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import gradio as gr
import core as core
from style import CSS, LANG_SYMBOLS, T_SYMBOLS, TITLE
demo = gr.Blocks(css=CSS)
with demo:
gr.HTML(TITLE)
gr.Markdown(
"This is a collection of multilingual evaluation results obtained using our fork of the LM-evaluation-harness (https://github.com/OpenGPTX/lm-evaluation-harness), based on V1 of the https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard.\
Note that currently, benchmarks are available in 21 European languages (Irish, Maltese, Croatian missing).",
elem_classes="markdown-text",
)
selected_tab = gr.State(value=0)
with gr.Column():
with gr.Row():
with gr.Column():
with gr.Row():
search_bar = gr.Textbox(
label="Search models",
placeholder=" 🔍 Separate multiple queries with ';' and press ENTER...",
show_label=True,
elem_id="search-bar",
)
model_types = gr.CheckboxGroup(
label="Select model type",
choices=[
(
f"Pretrained {T_SYMBOLS['pretrained']}",
T_SYMBOLS["pretrained"],
),
(f"Chat {T_SYMBOLS['chat']}", T_SYMBOLS["chat"]),
],
value=list(T_SYMBOLS.values()),
)
with gr.Row():
langs_bar = gr.CheckboxGroup(
choices=[(LANG_SYMBOLS.get(l, l), l) for l in core.languages_list],
value=core.languages_list,
label="Select languages to average over",
elem_id="column-select",
interactive=True,
scale=6,
)
with gr.Column(scale=1):
clear = gr.ClearButton(
langs_bar,
value="Deselect all languages",
size="sm",
scale=1,
)
select = gr.Button(value="Select all languages", size="sm", scale=1)
def update_bar(selected_tab):
if selected_tab in [0, 1]:
choices = [(LANG_SYMBOLS.get(l, l), l) for l in core.languages_list]
value = core.languages_list
else:
raise ValueError
langs_bar = gr.CheckboxGroup(
choices=choices,
value=value,
label="Select languages to average over",
elem_id="column-select",
interactive=True,
)
return langs_bar
select.click(update_bar, inputs=[selected_tab], outputs=langs_bar)
with gr.Row():
shown_tasks = gr.CheckboxGroup(
choices=[],
value=[],
label="Select tasks to show",
elem_id="column-select",
interactive=True,
scale=50,
)
fewshot = gr.Radio(
choices=[("0-Shot", False), ("Few-shot", True)],
value=True,
label="Select evaluation type",
scale=29,
)
clear = gr.ClearButton(shown_tasks, value="Deselect all tasks", size="sm", scale=21)
with gr.Tabs(elem_classes="tab-buttons") as tabs:
with gr.TabItem("🏅 LLM accuracy benchmark", elem_id="llm-benchmark-tab-table-acc", id=0) as acc:
leaderboard_table = gr.Dataframe()
with gr.TabItem(
"🌐 LLM translation benchmark",
elem_id="llm-benchmark-tab-table-misc",
id=1,
) as misc:
leaderboard_table_misc = gr.Dataframe()
demo.load(
core.update_task_groups_and_fewshot,
[gr.State(value=0), model_types, langs_bar, fewshot],
[shown_tasks, fewshot, selected_tab, model_types, langs_bar],
)
fewshot.change(
core.update_task_groups_and_fewshot,
[selected_tab, model_types, langs_bar, fewshot],
[shown_tasks, fewshot, selected_tab, model_types, langs_bar],
)
acc.select(
core.update_task_groups_and_fewshot,
inputs=[gr.State(value=0), model_types, langs_bar, fewshot],
outputs=[shown_tasks, fewshot, selected_tab, model_types, langs_bar],
)
misc.select(
core.update_task_groups_and_fewshot,
inputs=[gr.State(value=1), model_types, langs_bar, fewshot],
outputs=[shown_tasks, fewshot, selected_tab, model_types, langs_bar],
)
for comp, fn in [
(search_bar, "submit"),
(langs_bar, "change"),
(shown_tasks, "change"),
(fewshot, "change"),
(model_types, "change"),
]:
getattr(comp, fn)(
core.update_df,
[shown_tasks, search_bar, langs_bar, model_types, fewshot],
leaderboard_table,
)
getattr(comp, fn)(
core.update_df,
[shown_tasks, search_bar, langs_bar, model_types, fewshot],
leaderboard_table_misc,
)
gr.Blocks.load(
block=demo,
fn=core.update_df,
inputs=[shown_tasks, search_bar, langs_bar, model_types, fewshot],
outputs=leaderboard_table,
)
gr.Blocks.load(
block=demo,
fn=core.update_df,
inputs=[shown_tasks, search_bar, langs_bar, model_types, fewshot],
outputs=leaderboard_table_misc,
)
demo.launch()
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