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on
CPU Upgrade
eduagarcia
commited on
Commit
•
6da7311
1
Parent(s):
fbd2a73
Add new column: Main Language
Browse files- .gitignore +1 -0
- app.py +26 -5
- initial_queue.jsonl +196 -196
- src/display/utils.py +24 -1
- src/leaderboard/read_evals.py +6 -2
- src/submission/submit.py +3 -1
.gitignore
CHANGED
@@ -17,3 +17,4 @@ downloads/
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tasks_config/legal_config.yaml
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src/assets/model_counts.html
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tasks_config/legal_config.yaml
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src/assets/model_counts.html
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+
languages.jsonl
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app.py
CHANGED
@@ -29,7 +29,8 @@ from src.display.utils import (
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fields,
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WeightType,
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Precision,
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-
Tasks
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)
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from src.envs import (
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API,
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@@ -125,10 +126,11 @@ def update_table(
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type_query: list,
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precision_query: str,
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size_query: list,
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hide_models: list,
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query: str,
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):
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-
filtered_df = filter_models(df=hidden_df, type_query=type_query, size_query=size_query, precision_query=precision_query, hide_models=hide_models)
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filtered_df = filter_queries(query, filtered_df)
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filtered_df = update_leaderboard_avg_scores(filtered_df, columns)
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df = select_columns(filtered_df, columns)
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@@ -177,7 +179,7 @@ def filter_queries(query: str, filtered_df: pd.DataFrame):
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def filter_models(
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-
df: pd.DataFrame, type_query: list, size_query: list, precision_query: list, hide_models: list
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) -> pd.DataFrame:
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# Show all models
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if "Private or deleted" in hide_models:
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@@ -197,6 +199,7 @@ def filter_models(
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type_emoji = [t[0] for t in type_query]
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filtered_df = filtered_df.loc[df[AutoEvalColumn.model_type_symbol.name].isin(type_emoji)]
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filtered_df = filtered_df.loc[df[AutoEvalColumn.precision.name].isin(precision_query + ["None"])]
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numeric_interval = pd.IntervalIndex(sorted([NUMERIC_INTERVALS[s] for s in size_query]))
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params_column = pd.to_numeric(df[AutoEvalColumn.params.name], errors="coerce")
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@@ -225,6 +228,7 @@ leaderboard_df = filter_models(
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type_query=[t.to_str(" : ") for t in ModelType],
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size_query=list(NUMERIC_INTERVALS.keys()),
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precision_query=[i.value.name for i in Precision],
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hide_models=["Contains a merge/moerge", "Flagged"], # "Private or deleted", "Contains a merge/moerge", "Flagged"
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)
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@@ -289,6 +293,13 @@ with demo:
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interactive=True,
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elem_id="filter-columns-size",
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)
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leaderboard_table = gr.components.Dataframe(
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value=leaderboard_df[
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@@ -319,6 +330,7 @@ with demo:
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filter_columns_type,
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filter_columns_precision,
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filter_columns_size,
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hide_models,
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search_bar,
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],
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@@ -335,6 +347,7 @@ with demo:
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filter_columns_type,
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filter_columns_precision,
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filter_columns_size,
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hide_models,
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search_bar,
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],
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@@ -343,7 +356,7 @@ with demo:
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# Check query parameter once at startup and update search bar + hidden component
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demo.load(load_query, inputs=[], outputs=[search_bar, hidden_search_bar])
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-
for selector in [shown_columns, filter_columns_type, filter_columns_precision, filter_columns_size, hide_models]:
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selector.change(
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update_table,
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[
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@@ -352,6 +365,7 @@ with demo:
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filter_columns_type,
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filter_columns_precision,
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filter_columns_size,
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hide_models,
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search_bar,
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],
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@@ -455,6 +469,13 @@ with demo:
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value=ModelType.FT.to_str(" : "),
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interactive=True,
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)
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with gr.Column():
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precision = gr.Dropdown(
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@@ -472,7 +493,6 @@ with demo:
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interactive=True,
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)
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base_model_name_textbox = gr.Textbox(label="Base model (for delta or adapter weights)")
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-
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submit_button = gr.Button("Submit Eval")
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submission_result = gr.Markdown()
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submit_button.click(
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@@ -485,6 +505,7 @@ with demo:
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private,
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weight_type,
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model_type,
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],
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submission_result,
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)
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fields,
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WeightType,
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Precision,
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+
Tasks,
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+
Language
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)
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from src.envs import (
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API,
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type_query: list,
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precision_query: str,
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size_query: list,
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+
language_query: list,
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hide_models: list,
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query: str,
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):
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+
filtered_df = filter_models(df=hidden_df, type_query=type_query, size_query=size_query, language_query=language_query, precision_query=precision_query, hide_models=hide_models)
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filtered_df = filter_queries(query, filtered_df)
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filtered_df = update_leaderboard_avg_scores(filtered_df, columns)
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df = select_columns(filtered_df, columns)
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def filter_models(
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df: pd.DataFrame, type_query: list, size_query: list, language_query: list, precision_query: list, hide_models: list
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) -> pd.DataFrame:
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# Show all models
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if "Private or deleted" in hide_models:
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type_emoji = [t[0] for t in type_query]
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filtered_df = filtered_df.loc[df[AutoEvalColumn.model_type_symbol.name].isin(type_emoji)]
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filtered_df = filtered_df.loc[df[AutoEvalColumn.precision.name].isin(precision_query + ["None"])]
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+
filtered_df = filtered_df.loc[df[AutoEvalColumn.main_language.name].isin(language_query + ["None"])]
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numeric_interval = pd.IntervalIndex(sorted([NUMERIC_INTERVALS[s] for s in size_query]))
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params_column = pd.to_numeric(df[AutoEvalColumn.params.name], errors="coerce")
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type_query=[t.to_str(" : ") for t in ModelType],
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size_query=list(NUMERIC_INTERVALS.keys()),
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precision_query=[i.value.name for i in Precision],
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+
language_query=[i.value.name for i in Language],
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hide_models=["Contains a merge/moerge", "Flagged"], # "Private or deleted", "Contains a merge/moerge", "Flagged"
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)
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interactive=True,
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elem_id="filter-columns-size",
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)
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filter_columns_language = gr.CheckboxGroup(
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label="Model Main Language",
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choices=[i.value.name for i in Language],
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value=[i.value.name for i in Language],
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interactive=True,
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elem_id="filter-columns-language",
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)
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leaderboard_table = gr.components.Dataframe(
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value=leaderboard_df[
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filter_columns_type,
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filter_columns_precision,
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filter_columns_size,
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+
filter_columns_language,
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hide_models,
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search_bar,
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],
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filter_columns_type,
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filter_columns_precision,
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filter_columns_size,
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+
filter_columns_language,
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hide_models,
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search_bar,
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],
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# Check query parameter once at startup and update search bar + hidden component
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demo.load(load_query, inputs=[], outputs=[search_bar, hidden_search_bar])
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+
for selector in [shown_columns, filter_columns_type, filter_columns_precision, filter_columns_size, filter_columns_language, hide_models]:
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selector.change(
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update_table,
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[
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filter_columns_type,
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filter_columns_precision,
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filter_columns_size,
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+
filter_columns_language,
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hide_models,
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search_bar,
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],
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value=ModelType.FT.to_str(" : "),
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interactive=True,
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)
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+
main_language = gr.Dropdown(
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choices=[i.value.name for i in Language if i != Language.Unknown],
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label="Main Language",
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multiselect=False,
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value="English",
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interactive=True,
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)
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with gr.Column():
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precision = gr.Dropdown(
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interactive=True,
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)
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base_model_name_textbox = gr.Textbox(label="Base model (for delta or adapter weights)")
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submit_button = gr.Button("Submit Eval")
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submission_result = gr.Markdown()
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submit_button.click(
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private,
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weight_type,
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model_type,
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+
main_language
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],
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submission_result,
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)
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initial_queue.jsonl
CHANGED
@@ -1,215 +1,215 @@
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// 1- base models <=7B
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{"model": "TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
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-
{"model": "meta-llama/Llama-2-7b-hf", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
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-
{"model": "mistralai/Mistral-7B-v0.1", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
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-
{"model": "huggyllama/llama-7b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
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{"model": "openlm-research/open_llama_3b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
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{"model": "openlm-research/open_llama_3b_v2", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
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{"model": "openlm-research/open_llama_7b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
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{"model": "openlm-research/open_llama_7b_v2", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
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// 2 - Larger base models <= 13B
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{"model": "meta-llama/Llama-2-13b-hf", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
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{"model": "huggyllama/llama-13b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
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{"model": "openlm-research/open_llama_13b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
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{"model": "upstage/SOLAR-10.7B-v1.0", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
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// 3 - portuguese models
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{"model": "maritaca-ai/sabia-7b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)"}
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-
{"model": "dominguesm/canarim-7b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)"}
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-
{"model": "22h/open-cabrita3b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)"}
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-
{"model": "recogna-nlp/bode-7b-alpaca-pt-br", "base_model": "meta-llama/Llama-2-7b-chat-hf", "revision": "main", "precision": "float16", "weight_type": "Adapter", "model_type": "💬 : chat models (RLHF, DPO, IFT, ...)"}
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{"model": "recogna-nlp/bode-13b-alpaca-pt-br", "base_model": "meta-llama/Llama-2-13b-chat-hf", "revision": "main", "precision": "float16", "weight_type": "Adapter", "model_type": "💬 : chat models (RLHF, DPO, IFT, ...)"}
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{"model": "22h/cabrita_7b_pt_850000", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)"}
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-
{"model": "22h/cabrita-lora-v0-1", "base_model": "huggyllama/llama-7b", "revision": "main", "precision": "float16", "weight_type": "Adapter", "model_type": "🔶 : fine-tuned"}
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-
{"model": "wandgibaut/periquito-3B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)"}
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-
{"model": "nicolasdec/Cabra", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "💬 : chat models (RLHF, DPO, IFT, ...)"}
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{"model": "nicolasdec/cabra13b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "💬 : chat models (RLHF, DPO, IFT, ...)"}
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-
{"model": "lrds-code/samba-1.1B", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "💬 : chat models (RLHF, DPO, IFT, ...)"}
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-
{"model": "lrds-code/boana-7b-instruct", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "💬 : chat models (RLHF, DPO, IFT, ...)"}
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-
{"model": "nicholasKluge/Aira-2-portuguese-124M", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "💬 : chat models (RLHF, DPO, IFT, ...)"}
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-
{"model": "nicholasKluge/Aira-2-portuguese-560M", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "💬 : chat models (RLHF, DPO, IFT, ...)"}
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-
{"model": "nicholasKluge/Aira-2-portuguese-1B7", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "💬 : chat models (RLHF, DPO, IFT, ...)"}
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// other must-have <=7B
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{"model": "dynamofl/dynamo-8B-v0.1", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)"}
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-
{"model": "01-ai/Yi-6B", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
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-
{"model": "Unbabel/TowerBase-7B-v0.1", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)"}
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-
{"model": "tiiuae/falcon-7b", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
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-
{"model": "bigscience/bloom-560m", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
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-
{"model": "bigscience/bloom-1b7", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
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-
{"model": "bigscience/bloom-3b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
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-
{"model": "bigscience/bloom-7b1", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
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-
{"model": "stabilityai/stablelm-2-1_6b", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
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-
{"model": "stabilityai/stablelm-3b-4e1t", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
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// Larger base models >13B
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-
{"model": "mistralai/Mixtral-8x7B-v0.1", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
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-
{"model": "huggyllama/llama-30b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
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-
{"model": "01-ai/Yi-34B", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
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-
{"model": "meta-llama/Llama-2-70b-hf", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
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-
{"model": "huggyllama/llama-65b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
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// minors must
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-
{"model": "togethercomputer/RedPajama-INCITE-Base-3B-v1", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
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-
{"model": "togethercomputer/RedPajama-INCITE-7B-Base", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
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-
{"model": "DAMO-NLP-MT/polylm-1.7b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
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-
{"model": "DAMO-NLP-MT/polylm-13b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
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-
{"model": "Deci/DeciLM-6b", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🔶 : fine-tuned"}
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-
{"model": "Deci/DeciLM-7B", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🔶 : fine-tuned"}
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// multiple (ch-jp)/en bi/multi lingual models
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-
{"model": "internlm/internlm2-7b", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🔶 : fine-tuned"}
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-
{"model": "internlm/internlm2-base-7b", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
58 |
-
{"model": "internlm/internlm-7b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
59 |
-
{"model": "internlm/internlm2-20b", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🔶 : fine-tuned"}
|
60 |
-
{"model": "internlm/internlm2-base-20b", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
61 |
-
{"model": "internlm/internlm-20b", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
62 |
-
{"model": "Qwen/Qwen-1_8B", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
63 |
-
{"model": "Qwen/Qwen-7B", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
64 |
-
{"model": "Qwen/Qwen-14B", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
65 |
-
{"model": "xverse/XVERSE-7B", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
66 |
-
{"model": "xverse/XVERSE-13B", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
67 |
-
{"model": "xverse/XVERSE-13B-256K", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
68 |
-
{"model": "Skywork/Skywork-13B-base", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
69 |
-
{"model": "baichuan-inc/Baichuan-7B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
70 |
-
{"model": "baichuan-inc/Baichuan-13B-Base", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
71 |
-
{"model": "baichuan-inc/Baichuan2-7B-Base", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
72 |
-
{"model": "baichuan-inc/Baichuan2-13B-Base", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
73 |
-
{"model": "OrionStarAI/Orion-14B-Base", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
74 |
-
{"model": "deepseek-ai/deepseek-llm-7b-base", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
75 |
-
{"model": "deepseek-ai/deepseek-moe-16b-base", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
76 |
-
{"model": "BAAI/Aquila-7B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
77 |
-
{"model": "BAAI/Aquila2-7B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
78 |
-
{"model": "THUDM/chatglm3-6b-base", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
79 |
-
{"model": "THUDM/glm-2b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
80 |
-
{"model": "THUDM/glm-10b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
81 |
-
{"model": "fnlp/moss-moon-003-base", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
82 |
-
{"model": "fnlp/moss-base-7b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
83 |
// multiple chinese/jp large
|
84 |
-
{"model": "Qwen/Qwen-72B", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
85 |
-
{"model": "xverse/XVERSE-65B", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
86 |
-
{"model": "xverse/XVERSE-65B-2", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
87 |
-
{"model": "deepseek-ai/deepseek-llm-67b-base", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
88 |
-
{"model": "BAAI/Aquila2-34B", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
89 |
-
{"model": "BAAI/Aquila2-70B-Expr", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
90 |
// minors must 2
|
91 |
-
{"model": "gpt2", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
92 |
-
{"model": "t5-small", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
93 |
-
{"model": "t5-base", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
94 |
-
{"model": "t5-large", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
95 |
-
{"model": "google/mt5-small", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
96 |
-
{"model": "google/mt5-base", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
97 |
-
{"model": "google/mt5-large", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
98 |
//others
|
99 |
-
{"model": "NucleusAI/nucleus-22B-token-500B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
100 |
-
{"model": "EleutherAI/pythia-14m", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
101 |
-
{"model": "EleutherAI/pythia-70m-deduped", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
102 |
-
{"model": "EleutherAI/pythia-160m-deduped", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
103 |
-
{"model": "EleutherAI/pythia-410m-deduped", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
104 |
-
{"model": "EleutherAI/pythia-1b-deduped", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
105 |
-
{"model": "EleutherAI/pythia-2.8b-deduped", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
106 |
-
{"model": "EleutherAI/pythia-6.9b-deduped", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
107 |
-
{"model": "EleutherAI/pythia-12b-deduped", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
108 |
-
{"model": "EleutherAI/gpt-neo-125m", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
109 |
-
{"model": "EleutherAI/gpt-neo-1.3B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
110 |
-
{"model": "EleutherAI/gpt-neo-2.7B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
111 |
-
{"model": "EleutherAI/gpt-j-6b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
112 |
-
{"model": "EleutherAI/gpt-neox-20b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
113 |
-
{"model": "facebook/opt-125m", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
114 |
-
{"model": "facebook/opt-350m", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
115 |
-
{"model": "facebook/opt-1.3b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
116 |
-
{"model": "facebook/opt-2.7b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
117 |
-
{"model": "facebook/opt-6.7b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
118 |
-
{"model": "facebook/opt-13b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
119 |
-
{"model": "facebook/opt-30b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
120 |
//other large
|
121 |
-
{"model": "facebook/opt-66b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
122 |
-
{"model": "tiiuae/falcon-40b", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
123 |
// minors portuguese
|
124 |
-
{"model": "pierreguillou/gpt2-small-portuguese", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)"}
|
125 |
-
{"model": "pucpr/gpt2-bio-pt", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)"}
|
126 |
-
{"model": "unicamp-dl/ptt5-small-portuguese-vocab", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)"}
|
127 |
-
{"model": "unicamp-dl/ptt5-base-portuguese-vocab", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)"}
|
128 |
-
{"model": "unicamp-dl/ptt5-large-portuguese-vocab", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)"}
|
129 |
-
{"model": "unicamp-dl/ptt5-small-t5-vocab", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)"}
|
130 |
-
{"model": "unicamp-dl/ptt5-base-t5-vocab", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)"}
|
131 |
-
{"model": "unicamp-dl/ptt5-large-t5-vocab", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)"}
|
132 |
-
{"model": "josu/gpt-neo-pt-br", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)"}
|
133 |
-
{"model": "josu/gpt-neo-pt-1.3B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)"}
|
134 |
-
{"model": "monilouise/opt125M_portuguese", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)"}
|
135 |
-
{"model": "HeyLucasLeao/gpt-neo-small-portuguese", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)"}
|
136 |
// other langs (es/Ko/Jp/nordic)
|
137 |
-
{"model": "projecte-aina/FLOR-760M", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)"}
|
138 |
-
{"model": "projecte-aina/FLOR-1.3B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)"}
|
139 |
-
{"model": "projecte-aina/FLOR-6.3B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)"}
|
140 |
-
{"model": "projecte-aina/aguila-7b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)"}
|
141 |
-
{"model": "EleutherAI/polyglot-ko-12.8b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
142 |
-
{"model": "matsuo-lab/weblab-10b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
143 |
-
{"model": "pfnet/plamo-13b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
144 |
-
{"model": "AI-Sweden-Models/gpt-sw3-6.7b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
145 |
-
{"model": "AI-Sweden-Models/gpt-sw3-6.7b-v2", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
146 |
-
{"model": "AI-Sweden-Models/gpt-sw3-20b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
147 |
-
{"model": "AI-Sweden-Models/gpt-sw3-40b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
148 |
-
{"model": "OpenLLM-France/Claire-Mistral-7B-0.1", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)"}
|
149 |
-
{"model": "OpenLLM-France/Claire-7B-0.1", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)"}
|
150 |
// huge models:
|
151 |
//{"model": "bigscience/bloom", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
152 |
//{"model": "tiiuae/falcon-180B", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
153 |
//{"model": "facebook/galactica-120b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
154 |
//random chat models
|
155 |
-
{"model": "openchat/openchat-3.5-0106", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "💬 : chat models (RLHF, DPO, IFT, ...)"}
|
156 |
//other 2
|
157 |
-
{"model": "stabilityai/stablelm-base-alpha-3b-v2", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
158 |
-
{"model": "stabilityai/stablelm-base-alpha-7b-v2", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
159 |
-
{"model": "stabilityai/stablelm-base-alpha-3b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
160 |
-
{"model": "stabilityai/stablelm-base-alpha-7b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
161 |
-
{"model": "openai-community/openai-gpt", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
162 |
-
{"model": "openai-community/gpt2-medium", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
163 |
-
{"model": "openai-community/gpt2-large", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
164 |
-
{"model": "openai-community/gpt2-xl", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
165 |
-
{"model": "microsoft/phi-1", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
166 |
-
{"model": "microsoft/phi-1_5", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
167 |
-
{"model": "microsoft/phi-2", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
168 |
-
{"model": "mosaicml/mpt-7b", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
169 |
-
{"model": "mosaicml/mpt-30b", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
170 |
-
{"model": "mosaicml/mpt-7b-8k", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
171 |
-
{"model": "01-ai/Yi-6B-200K", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
172 |
-
{"model": "01-ai/Yi-34B-200K", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
173 |
-
{"model": "google/t5-v1_1-base", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
174 |
-
{"model": "google/t5-v1_1-small", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
175 |
-
{"model": "google/t5-v1_1-large", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
176 |
-
{"model": "google/t5-v1_1-xl", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
177 |
-
{"model": "google/t5-v1_1-xxl", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
178 |
-
{"model": "google/mt5-xl", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
179 |
-
{"model": "google/mt5-xxl", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
180 |
-
{"model": "google/umt5-small", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
181 |
-
{"model": "google/umt5-base", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
182 |
-
{"model": "google/umt5-xl", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
183 |
-
{"model": "google/umt5-xxl", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
184 |
-
{"model": "AdaptLLM/law-LLM", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🔶 : fine-tuned"}
|
185 |
-
{"model": "AdaptLLM/medicine-LLM", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🔶 : fine-tuned"}
|
186 |
-
{"model": "AdaptLLM/finance-LLM", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🔶 : fine-tuned"}
|
187 |
-
{"model": "AdaptLLM/law-LLM-13B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🔶 : fine-tuned"}
|
188 |
-
{"model": "AdaptLLM/medicine-LLM-13B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🔶 : fine-tuned"}
|
189 |
-
{"model": "AdaptLLM/finance-LLM-13B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🔶 : fine-tuned"}
|
190 |
-
{"model": "cerebras/Cerebras-GPT-111M", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
191 |
-
{"model": "cerebras/Cerebras-GPT-256M", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
192 |
-
{"model": "cerebras/Cerebras-GPT-590M", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
193 |
-
{"model": "cerebras/Cerebras-GPT-1.3B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
194 |
-
{"model": "cerebras/Cerebras-GPT-2.7B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
195 |
-
{"model": "cerebras/Cerebras-GPT-6.7B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
196 |
-
{"model": "cerebras/Cerebras-GPT-13B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
197 |
-
{"model": "cerebras/btlm-3b-8k-base", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
198 |
-
{"model": "ai-forever/mGPT-13B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
199 |
-
{"model": "ai-forever/mGPT", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
200 |
-
{"model": "EleutherAI/pythia-70m", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
201 |
-
{"model": "EleutherAI/pythia-160m", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
202 |
-
{"model": "EleutherAI/pythia-410m", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
203 |
-
{"model": "EleutherAI/pythia-1b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
204 |
-
{"model": "EleutherAI/pythia-2.8b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
205 |
-
{"model": "EleutherAI/pythia-6.9b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
206 |
-
{"model": "EleutherAI/pythia-12b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
207 |
-
{"model": "facebook/galactica-125m", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
208 |
-
{"model": "facebook/galactica-1.3b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
209 |
-
{"model": "facebook/galactica-6.7b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
210 |
-
{"model": "facebook/galactica-30b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
211 |
-
{"model": "facebook/xglm-564M", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
212 |
-
{"model": "facebook/xglm-1.7B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
213 |
-
{"model": "facebook/xglm-2.9B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
214 |
-
{"model": "facebook/xglm-4.5B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
215 |
-
{"model": "facebook/xglm-7.5B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
|
|
1 |
// 1- base models <=7B
|
2 |
+
{"model": "TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
3 |
+
{"model": "meta-llama/Llama-2-7b-hf", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
4 |
+
{"model": "mistralai/Mistral-7B-v0.1", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
5 |
+
{"model": "huggyllama/llama-7b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
6 |
+
{"model": "openlm-research/open_llama_3b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
7 |
+
{"model": "openlm-research/open_llama_3b_v2", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
8 |
+
{"model": "openlm-research/open_llama_7b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
9 |
+
{"model": "openlm-research/open_llama_7b_v2", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
10 |
// 2 - Larger base models <= 13B
|
11 |
+
{"model": "meta-llama/Llama-2-13b-hf", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
12 |
+
{"model": "huggyllama/llama-13b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
13 |
+
{"model": "openlm-research/open_llama_13b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
14 |
+
{"model": "upstage/SOLAR-10.7B-v1.0", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
15 |
// 3 - portuguese models
|
16 |
+
{"model": "maritaca-ai/sabia-7b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)", "main_language": "Portuguese"}
|
17 |
+
{"model": "dominguesm/canarim-7b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)", "main_language": "Portuguese"}
|
18 |
+
{"model": "22h/open-cabrita3b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)", "main_language": "Portuguese"}
|
19 |
+
{"model": "recogna-nlp/bode-7b-alpaca-pt-br", "base_model": "meta-llama/Llama-2-7b-chat-hf", "revision": "main", "precision": "float16", "weight_type": "Adapter", "model_type": "💬 : chat models (RLHF, DPO, IFT, ...)", "main_language": "Portuguese"}
|
20 |
+
{"model": "recogna-nlp/bode-13b-alpaca-pt-br", "base_model": "meta-llama/Llama-2-13b-chat-hf", "revision": "main", "precision": "float16", "weight_type": "Adapter", "model_type": "💬 : chat models (RLHF, DPO, IFT, ...)", "main_language": "Portuguese"}
|
21 |
+
{"model": "22h/cabrita_7b_pt_850000", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)", "main_language": "Portuguese"}
|
22 |
+
{"model": "22h/cabrita-lora-v0-1", "base_model": "huggyllama/llama-7b", "revision": "main", "precision": "float16", "weight_type": "Adapter", "model_type": "🔶 : fine-tuned", "main_language": "Portuguese"}
|
23 |
+
{"model": "wandgibaut/periquito-3B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)", "main_language": "Portuguese"}
|
24 |
+
{"model": "nicolasdec/Cabra", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "💬 : chat models (RLHF, DPO, IFT, ...)", "main_language": "Portuguese"}
|
25 |
+
{"model": "nicolasdec/cabra13b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "💬 : chat models (RLHF, DPO, IFT, ...)", "main_language": "Portuguese"}
|
26 |
+
{"model": "lrds-code/samba-1.1B", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "💬 : chat models (RLHF, DPO, IFT, ...)", "main_language": "Portuguese"}
|
27 |
+
{"model": "lrds-code/boana-7b-instruct", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "💬 : chat models (RLHF, DPO, IFT, ...)", "main_language": "Portuguese"}
|
28 |
+
{"model": "nicholasKluge/Aira-2-portuguese-124M", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "💬 : chat models (RLHF, DPO, IFT, ...)", "main_language": "Portuguese"}
|
29 |
+
{"model": "nicholasKluge/Aira-2-portuguese-560M", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "💬 : chat models (RLHF, DPO, IFT, ...)", "main_language": "Portuguese"}
|
30 |
+
{"model": "nicholasKluge/Aira-2-portuguese-1B7", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "💬 : chat models (RLHF, DPO, IFT, ...)", "main_language": "Portuguese"}
|
31 |
// other must-have <=7B
|
32 |
+
{"model": "dynamofl/dynamo-8B-v0.1", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)", "main_language": "English"}
|
33 |
+
{"model": "01-ai/Yi-6B", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
34 |
+
{"model": "Unbabel/TowerBase-7B-v0.1", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)", "main_language": "English"}
|
35 |
+
{"model": "tiiuae/falcon-7b", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
36 |
+
{"model": "bigscience/bloom-560m", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
37 |
+
{"model": "bigscience/bloom-1b7", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
38 |
+
{"model": "bigscience/bloom-3b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
39 |
+
{"model": "bigscience/bloom-7b1", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
40 |
+
{"model": "stabilityai/stablelm-2-1_6b", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
41 |
+
{"model": "stabilityai/stablelm-3b-4e1t", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
42 |
// Larger base models >13B
|
43 |
+
{"model": "mistralai/Mixtral-8x7B-v0.1", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
44 |
+
{"model": "huggyllama/llama-30b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
45 |
+
{"model": "01-ai/Yi-34B", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
46 |
+
{"model": "meta-llama/Llama-2-70b-hf", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
47 |
+
{"model": "huggyllama/llama-65b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
48 |
// minors must
|
49 |
+
{"model": "togethercomputer/RedPajama-INCITE-Base-3B-v1", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
50 |
+
{"model": "togethercomputer/RedPajama-INCITE-7B-Base", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
51 |
+
{"model": "DAMO-NLP-MT/polylm-1.7b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
52 |
+
{"model": "DAMO-NLP-MT/polylm-13b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
53 |
+
{"model": "Deci/DeciLM-6b", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🔶 : fine-tuned", "main_language": "English"}
|
54 |
+
{"model": "Deci/DeciLM-7B", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🔶 : fine-tuned", "main_language": "English"}
|
55 |
// multiple (ch-jp)/en bi/multi lingual models
|
56 |
+
{"model": "internlm/internlm2-7b", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🔶 : fine-tuned", "main_language": "?"}
|
57 |
+
{"model": "internlm/internlm2-base-7b", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "?"}
|
58 |
+
{"model": "internlm/internlm-7b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "?"}
|
59 |
+
{"model": "internlm/internlm2-20b", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🔶 : fine-tuned", "main_language": "?"}
|
60 |
+
{"model": "internlm/internlm2-base-20b", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "?"}
|
61 |
+
{"model": "internlm/internlm-20b", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "?"}
|
62 |
+
{"model": "Qwen/Qwen-1_8B", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "Chinese"}
|
63 |
+
{"model": "Qwen/Qwen-7B", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "Chinese"}
|
64 |
+
{"model": "Qwen/Qwen-14B", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "Chinese"}
|
65 |
+
{"model": "xverse/XVERSE-7B", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "?"}
|
66 |
+
{"model": "xverse/XVERSE-13B", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "?"}
|
67 |
+
{"model": "xverse/XVERSE-13B-256K", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "?"}
|
68 |
+
{"model": "Skywork/Skywork-13B-base", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "?"}
|
69 |
+
{"model": "baichuan-inc/Baichuan-7B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "Chinese"}
|
70 |
+
{"model": "baichuan-inc/Baichuan-13B-Base", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "?"}
|
71 |
+
{"model": "baichuan-inc/Baichuan2-7B-Base", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "Chinese"}
|
72 |
+
{"model": "baichuan-inc/Baichuan2-13B-Base", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "Chinese"}
|
73 |
+
{"model": "OrionStarAI/Orion-14B-Base", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "Chinese"}
|
74 |
+
{"model": "deepseek-ai/deepseek-llm-7b-base", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "?"}
|
75 |
+
{"model": "deepseek-ai/deepseek-moe-16b-base", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "?"}
|
76 |
+
{"model": "BAAI/Aquila-7B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "?"}
|
77 |
+
{"model": "BAAI/Aquila2-7B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "?"}
|
78 |
+
{"model": "THUDM/chatglm3-6b-base", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "Chinese"}
|
79 |
+
{"model": "THUDM/glm-2b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
80 |
+
{"model": "THUDM/glm-10b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
81 |
+
{"model": "fnlp/moss-moon-003-base", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "?"}
|
82 |
+
{"model": "fnlp/moss-base-7b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "?"}
|
83 |
// multiple chinese/jp large
|
84 |
+
{"model": "Qwen/Qwen-72B", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "Chinese"}
|
85 |
+
{"model": "xverse/XVERSE-65B", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "?"}
|
86 |
+
{"model": "xverse/XVERSE-65B-2", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "?"}
|
87 |
+
{"model": "deepseek-ai/deepseek-llm-67b-base", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "?"}
|
88 |
+
{"model": "BAAI/Aquila2-34B", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "?"}
|
89 |
+
{"model": "BAAI/Aquila2-70B-Expr", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "?"}
|
90 |
// minors must 2
|
91 |
+
{"model": "gpt2", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
92 |
+
{"model": "t5-small", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
93 |
+
{"model": "t5-base", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
94 |
+
{"model": "t5-large", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
95 |
+
{"model": "google/mt5-small", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
96 |
+
{"model": "google/mt5-base", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
97 |
+
{"model": "google/mt5-large", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
98 |
//others
|
99 |
+
{"model": "NucleusAI/nucleus-22B-token-500B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
100 |
+
{"model": "EleutherAI/pythia-14m", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
101 |
+
{"model": "EleutherAI/pythia-70m-deduped", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
102 |
+
{"model": "EleutherAI/pythia-160m-deduped", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
103 |
+
{"model": "EleutherAI/pythia-410m-deduped", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
104 |
+
{"model": "EleutherAI/pythia-1b-deduped", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
105 |
+
{"model": "EleutherAI/pythia-2.8b-deduped", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
106 |
+
{"model": "EleutherAI/pythia-6.9b-deduped", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
107 |
+
{"model": "EleutherAI/pythia-12b-deduped", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
108 |
+
{"model": "EleutherAI/gpt-neo-125m", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
109 |
+
{"model": "EleutherAI/gpt-neo-1.3B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
110 |
+
{"model": "EleutherAI/gpt-neo-2.7B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
111 |
+
{"model": "EleutherAI/gpt-j-6b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
112 |
+
{"model": "EleutherAI/gpt-neox-20b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
113 |
+
{"model": "facebook/opt-125m", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
114 |
+
{"model": "facebook/opt-350m", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
115 |
+
{"model": "facebook/opt-1.3b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
116 |
+
{"model": "facebook/opt-2.7b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
117 |
+
{"model": "facebook/opt-6.7b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
118 |
+
{"model": "facebook/opt-13b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
119 |
+
{"model": "facebook/opt-30b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
120 |
//other large
|
121 |
+
{"model": "facebook/opt-66b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
122 |
+
{"model": "tiiuae/falcon-40b", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
123 |
// minors portuguese
|
124 |
+
{"model": "pierreguillou/gpt2-small-portuguese", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)", "main_language": "Portuguese"}
|
125 |
+
{"model": "pucpr/gpt2-bio-pt", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)", "main_language": "Portuguese"}
|
126 |
+
{"model": "unicamp-dl/ptt5-small-portuguese-vocab", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)", "main_language": "Portuguese"}
|
127 |
+
{"model": "unicamp-dl/ptt5-base-portuguese-vocab", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)", "main_language": "Portuguese"}
|
128 |
+
{"model": "unicamp-dl/ptt5-large-portuguese-vocab", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)", "main_language": "Portuguese"}
|
129 |
+
{"model": "unicamp-dl/ptt5-small-t5-vocab", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)", "main_language": "Portuguese"}
|
130 |
+
{"model": "unicamp-dl/ptt5-base-t5-vocab", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)", "main_language": "Portuguese"}
|
131 |
+
{"model": "unicamp-dl/ptt5-large-t5-vocab", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)", "main_language": "Portuguese"}
|
132 |
+
{"model": "josu/gpt-neo-pt-br", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)", "main_language": "Portuguese"}
|
133 |
+
{"model": "josu/gpt-neo-pt-1.3B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)", "main_language": "Portuguese"}
|
134 |
+
{"model": "monilouise/opt125M_portuguese", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)", "main_language": "Portuguese"}
|
135 |
+
{"model": "HeyLucasLeao/gpt-neo-small-portuguese", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)", "main_language": "Portuguese"}
|
136 |
// other langs (es/Ko/Jp/nordic)
|
137 |
+
{"model": "projecte-aina/FLOR-760M", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)", "main_language": "Spanish"}
|
138 |
+
{"model": "projecte-aina/FLOR-1.3B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)", "main_language": "Spanish"}
|
139 |
+
{"model": "projecte-aina/FLOR-6.3B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)", "main_language": "Spanish"}
|
140 |
+
{"model": "projecte-aina/aguila-7b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)", "main_language": "Spanish"}
|
141 |
+
{"model": "EleutherAI/polyglot-ko-12.8b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "Other"}
|
142 |
+
{"model": "matsuo-lab/weblab-10b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "Other"}
|
143 |
+
{"model": "pfnet/plamo-13b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
144 |
+
{"model": "AI-Sweden-Models/gpt-sw3-6.7b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
145 |
+
{"model": "AI-Sweden-Models/gpt-sw3-6.7b-v2", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
146 |
+
{"model": "AI-Sweden-Models/gpt-sw3-20b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
147 |
+
{"model": "AI-Sweden-Models/gpt-sw3-40b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
148 |
+
{"model": "OpenLLM-France/Claire-Mistral-7B-0.1", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)", "main_language": "Other"}
|
149 |
+
{"model": "OpenLLM-France/Claire-7B-0.1", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🆎 : language adapted models (FP, FT, ...)", "main_language": "Other"}
|
150 |
// huge models:
|
151 |
//{"model": "bigscience/bloom", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
152 |
//{"model": "tiiuae/falcon-180B", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
153 |
//{"model": "facebook/galactica-120b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained"}
|
154 |
//random chat models
|
155 |
+
{"model": "openchat/openchat-3.5-0106", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "💬 : chat models (RLHF, DPO, IFT, ...)", "main_language": "English"}
|
156 |
//other 2
|
157 |
+
{"model": "stabilityai/stablelm-base-alpha-3b-v2", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
158 |
+
{"model": "stabilityai/stablelm-base-alpha-7b-v2", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
159 |
+
{"model": "stabilityai/stablelm-base-alpha-3b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
160 |
+
{"model": "stabilityai/stablelm-base-alpha-7b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
161 |
+
{"model": "openai-community/openai-gpt", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
162 |
+
{"model": "openai-community/gpt2-medium", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
163 |
+
{"model": "openai-community/gpt2-large", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
164 |
+
{"model": "openai-community/gpt2-xl", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
165 |
+
{"model": "microsoft/phi-1", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
166 |
+
{"model": "microsoft/phi-1_5", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
167 |
+
{"model": "microsoft/phi-2", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
168 |
+
{"model": "mosaicml/mpt-7b", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
169 |
+
{"model": "mosaicml/mpt-30b", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
170 |
+
{"model": "mosaicml/mpt-7b-8k", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
171 |
+
{"model": "01-ai/Yi-6B-200K", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
172 |
+
{"model": "01-ai/Yi-34B-200K", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
173 |
+
{"model": "google/t5-v1_1-base", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
174 |
+
{"model": "google/t5-v1_1-small", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
175 |
+
{"model": "google/t5-v1_1-large", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
176 |
+
{"model": "google/t5-v1_1-xl", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
177 |
+
{"model": "google/t5-v1_1-xxl", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
178 |
+
{"model": "google/mt5-xl", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
179 |
+
{"model": "google/mt5-xxl", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
180 |
+
{"model": "google/umt5-small", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
181 |
+
{"model": "google/umt5-base", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
182 |
+
{"model": "google/umt5-xl", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
183 |
+
{"model": "google/umt5-xxl", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
184 |
+
{"model": "AdaptLLM/law-LLM", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🔶 : fine-tuned", "main_language": "English"}
|
185 |
+
{"model": "AdaptLLM/medicine-LLM", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🔶 : fine-tuned", "main_language": "English"}
|
186 |
+
{"model": "AdaptLLM/finance-LLM", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🔶 : fine-tuned", "main_language": "English"}
|
187 |
+
{"model": "AdaptLLM/law-LLM-13B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🔶 : fine-tuned", "main_language": "English"}
|
188 |
+
{"model": "AdaptLLM/medicine-LLM-13B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🔶 : fine-tuned", "main_language": "English"}
|
189 |
+
{"model": "AdaptLLM/finance-LLM-13B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🔶 : fine-tuned", "main_language": "English"}
|
190 |
+
{"model": "cerebras/Cerebras-GPT-111M", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
191 |
+
{"model": "cerebras/Cerebras-GPT-256M", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
192 |
+
{"model": "cerebras/Cerebras-GPT-590M", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
193 |
+
{"model": "cerebras/Cerebras-GPT-1.3B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
194 |
+
{"model": "cerebras/Cerebras-GPT-2.7B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
195 |
+
{"model": "cerebras/Cerebras-GPT-6.7B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
196 |
+
{"model": "cerebras/Cerebras-GPT-13B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
197 |
+
{"model": "cerebras/btlm-3b-8k-base", "base_model": "", "revision": "main", "precision": "bfloat16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
198 |
+
{"model": "ai-forever/mGPT-13B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
199 |
+
{"model": "ai-forever/mGPT", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
200 |
+
{"model": "EleutherAI/pythia-70m", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
201 |
+
{"model": "EleutherAI/pythia-160m", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
202 |
+
{"model": "EleutherAI/pythia-410m", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
203 |
+
{"model": "EleutherAI/pythia-1b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
204 |
+
{"model": "EleutherAI/pythia-2.8b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
205 |
+
{"model": "EleutherAI/pythia-6.9b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
206 |
+
{"model": "EleutherAI/pythia-12b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
207 |
+
{"model": "facebook/galactica-125m", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
208 |
+
{"model": "facebook/galactica-1.3b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
209 |
+
{"model": "facebook/galactica-6.7b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
210 |
+
{"model": "facebook/galactica-30b", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
211 |
+
{"model": "facebook/xglm-564M", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
212 |
+
{"model": "facebook/xglm-1.7B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
213 |
+
{"model": "facebook/xglm-2.9B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
214 |
+
{"model": "facebook/xglm-4.5B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
215 |
+
{"model": "facebook/xglm-7.5B", "base_model": "", "revision": "main", "precision": "float16", "weight_type": "Original", "model_type": "🟢 : pretrained", "main_language": "English"}
|
src/display/utils.py
CHANGED
@@ -66,6 +66,7 @@ auto_eval_column_dict.append(["dummy", ColumnContent, ColumnContent("Model Name"
|
|
66 |
if GET_ORIGINAL_HF_LEADERBOARD_EVAL_RESULTS:
|
67 |
auto_eval_column_dict.append(["original_benchmark_average", ColumnContent, ColumnContent("🤗 Leaderboard Average", "number", False)])
|
68 |
auto_eval_column_dict.append(["npm", ColumnContent, ColumnContent("NPM (Average) ⬆️", "number", False)])
|
|
|
69 |
|
70 |
# We use make dataclass to dynamically fill the scores from Tasks
|
71 |
AutoEvalColumn = make_dataclass("AutoEvalColumn", auto_eval_column_dict, frozen=True)
|
@@ -103,7 +104,8 @@ baseline_row = {
|
|
103 |
AutoEvalColumn.license.name: "",
|
104 |
AutoEvalColumn.still_on_hub.name: False,
|
105 |
AutoEvalColumn.moe.name: False,
|
106 |
-
AutoEvalColumn.eval_time.name: 0.0
|
|
|
107 |
}
|
108 |
|
109 |
baseline_list = []
|
@@ -152,6 +154,7 @@ human_baseline_row = {
|
|
152 |
AutoEvalColumn.still_on_hub.name: False,
|
153 |
AutoEvalColumn.moe.name: False,
|
154 |
AutoEvalColumn.eval_time.name: 0.0,
|
|
|
155 |
}
|
156 |
|
157 |
baseline_list = []
|
@@ -225,7 +228,27 @@ class Precision(Enum):
|
|
225 |
return Precision.qt_GPTQ
|
226 |
return Precision.Unknown
|
227 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
228 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
229 |
|
230 |
|
231 |
# Column selection
|
|
|
66 |
if GET_ORIGINAL_HF_LEADERBOARD_EVAL_RESULTS:
|
67 |
auto_eval_column_dict.append(["original_benchmark_average", ColumnContent, ColumnContent("🤗 Leaderboard Average", "number", False)])
|
68 |
auto_eval_column_dict.append(["npm", ColumnContent, ColumnContent("NPM (Average) ⬆️", "number", False)])
|
69 |
+
auto_eval_column_dict.append(["main_language", ColumnContent, ColumnContent("Main Language", "str", False)])
|
70 |
|
71 |
# We use make dataclass to dynamically fill the scores from Tasks
|
72 |
AutoEvalColumn = make_dataclass("AutoEvalColumn", auto_eval_column_dict, frozen=True)
|
|
|
104 |
AutoEvalColumn.license.name: "",
|
105 |
AutoEvalColumn.still_on_hub.name: False,
|
106 |
AutoEvalColumn.moe.name: False,
|
107 |
+
AutoEvalColumn.eval_time.name: 0.0,
|
108 |
+
AutoEvalColumn.main_language.name: "?"
|
109 |
}
|
110 |
|
111 |
baseline_list = []
|
|
|
154 |
AutoEvalColumn.still_on_hub.name: False,
|
155 |
AutoEvalColumn.moe.name: False,
|
156 |
AutoEvalColumn.eval_time.name: 0.0,
|
157 |
+
AutoEvalColumn.main_language.name: "?",
|
158 |
}
|
159 |
|
160 |
baseline_list = []
|
|
|
228 |
return Precision.qt_GPTQ
|
229 |
return Precision.Unknown
|
230 |
|
231 |
+
class Language(Enum):
|
232 |
+
English = ModelDetails("English")
|
233 |
+
Portuguese = ModelDetails("Portuguese")
|
234 |
+
Spanish = ModelDetails("Spanish")
|
235 |
+
Chinese = ModelDetails("Chinese")
|
236 |
+
Other = ModelDetails("Other")
|
237 |
+
Unknown = ModelDetails("?")
|
238 |
|
239 |
+
def from_str(language):
|
240 |
+
language = language.lower().replace('-', '').replace('_', '')
|
241 |
+
if language in ["pt", "ptpt", "ptbr", "portuguese"]:
|
242 |
+
return Language.Portuguese
|
243 |
+
if language in ["en", "enus", "engb", "english", ]:
|
244 |
+
return Language.English
|
245 |
+
if language in ["es", "spanish"]:
|
246 |
+
return Language.Spanish
|
247 |
+
if language in ["zh", "chinese"]:
|
248 |
+
return Language.Chinese
|
249 |
+
if language in ["other", "multi", "multilingual"]:
|
250 |
+
return Language.Other
|
251 |
+
return Language.Unknown
|
252 |
|
253 |
|
254 |
# Column selection
|
src/leaderboard/read_evals.py
CHANGED
@@ -4,6 +4,7 @@ import math
|
|
4 |
import os
|
5 |
from dataclasses import dataclass
|
6 |
from typing import List
|
|
|
7 |
|
8 |
import dateutil
|
9 |
import numpy as np
|
@@ -11,7 +12,7 @@ import numpy as np
|
|
11 |
from huggingface_hub import ModelCard
|
12 |
|
13 |
from src.display.formatting import make_clickable_model
|
14 |
-
from src.display.utils import AutoEvalColumn, ModelType, Tasks, Precision, WeightType, ORIGINAL_TASKS
|
15 |
from src.envs import GET_ORIGINAL_HF_LEADERBOARD_EVAL_RESULTS, SHOW_INCOMPLETE_EVALS
|
16 |
|
17 |
@dataclass
|
@@ -26,6 +27,7 @@ class EvalResult:
|
|
26 |
precision: Precision = Precision.Unknown
|
27 |
model_type: ModelType = ModelType.Unknown # Pretrained, fine tuned, ...
|
28 |
weight_type: WeightType = WeightType.Original # Original or Adapter
|
|
|
29 |
architecture: str = "Unknown" # From config file
|
30 |
license: str = "?"
|
31 |
likes: int = 0
|
@@ -137,6 +139,7 @@ class EvalResult:
|
|
137 |
self.architecture = request.get("architectures", "Unknown")
|
138 |
self.status = request.get("status", "FAILED")
|
139 |
self.hidden = request.get("hidden", False)
|
|
|
140 |
except Exception as e:
|
141 |
self.status = "FAILED"
|
142 |
print(f"Could not find request file for {self.org}/{self.model}")
|
@@ -188,7 +191,8 @@ class EvalResult:
|
|
188 |
AutoEvalColumn.moe.name: ("moe" in self.tags if self.tags else False) or "moe" in self.full_model.lower(),
|
189 |
AutoEvalColumn.flagged.name: self.flagged,
|
190 |
AutoEvalColumn.eval_time.name: self.eval_time,
|
191 |
-
AutoEvalColumn.npm.name: npm
|
|
|
192 |
}
|
193 |
|
194 |
for task in Tasks:
|
|
|
4 |
import os
|
5 |
from dataclasses import dataclass
|
6 |
from typing import List
|
7 |
+
import traceback
|
8 |
|
9 |
import dateutil
|
10 |
import numpy as np
|
|
|
12 |
from huggingface_hub import ModelCard
|
13 |
|
14 |
from src.display.formatting import make_clickable_model
|
15 |
+
from src.display.utils import AutoEvalColumn, ModelType, Tasks, Precision, Language, WeightType, ORIGINAL_TASKS
|
16 |
from src.envs import GET_ORIGINAL_HF_LEADERBOARD_EVAL_RESULTS, SHOW_INCOMPLETE_EVALS
|
17 |
|
18 |
@dataclass
|
|
|
27 |
precision: Precision = Precision.Unknown
|
28 |
model_type: ModelType = ModelType.Unknown # Pretrained, fine tuned, ...
|
29 |
weight_type: WeightType = WeightType.Original # Original or Adapter
|
30 |
+
main_language: Language = Language.Unknown
|
31 |
architecture: str = "Unknown" # From config file
|
32 |
license: str = "?"
|
33 |
likes: int = 0
|
|
|
139 |
self.architecture = request.get("architectures", "Unknown")
|
140 |
self.status = request.get("status", "FAILED")
|
141 |
self.hidden = request.get("hidden", False)
|
142 |
+
self.main_language = request.get("main_language", "?")
|
143 |
except Exception as e:
|
144 |
self.status = "FAILED"
|
145 |
print(f"Could not find request file for {self.org}/{self.model}")
|
|
|
191 |
AutoEvalColumn.moe.name: ("moe" in self.tags if self.tags else False) or "moe" in self.full_model.lower(),
|
192 |
AutoEvalColumn.flagged.name: self.flagged,
|
193 |
AutoEvalColumn.eval_time.name: self.eval_time,
|
194 |
+
AutoEvalColumn.npm.name: npm,
|
195 |
+
AutoEvalColumn.main_language.name: self.main_language
|
196 |
}
|
197 |
|
198 |
for task in Tasks:
|
src/submission/submit.py
CHANGED
@@ -27,7 +27,8 @@ def add_new_eval(
|
|
27 |
private: bool,
|
28 |
weight_type: str,
|
29 |
model_type: str,
|
30 |
-
|
|
|
31 |
):
|
32 |
global REQUESTED_MODELS
|
33 |
global USERS_TO_SUBMISSION_DATES
|
@@ -119,6 +120,7 @@ def add_new_eval(
|
|
119 |
"params": model_size,
|
120 |
"architectures": architecture,
|
121 |
"weight_type": weight_type,
|
|
|
122 |
"status": "PENDING",
|
123 |
"submitted_time": current_time,
|
124 |
"model_type": model_type,
|
|
|
27 |
private: bool,
|
28 |
weight_type: str,
|
29 |
model_type: str,
|
30 |
+
main_language: str,
|
31 |
+
source="leaderboard",
|
32 |
):
|
33 |
global REQUESTED_MODELS
|
34 |
global USERS_TO_SUBMISSION_DATES
|
|
|
120 |
"params": model_size,
|
121 |
"architectures": architecture,
|
122 |
"weight_type": weight_type,
|
123 |
+
"main_language": main_language,
|
124 |
"status": "PENDING",
|
125 |
"submitted_time": current_time,
|
126 |
"model_type": model_type,
|