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upload gpt-4o-mini battles
Browse files- .gitattributes +3 -0
- README.md +3 -13
- app.py +3 -184
- data/sample_gpt-4o-mini.jsonl +3 -0
- data/sample_if.jsonl +0 -0
- data/sample_math.jsonl +0 -0
.gitattributes
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@@ -33,3 +33,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.md filter=lfs diff=lfs merge=lfs -text
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*.py filter=lfs diff=lfs merge=lfs -text
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*.jsonl filter=lfs diff=lfs merge=lfs -text
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README.md
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colorFrom: indigo
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colorTo: green
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sdk: gradio
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sdk_version: 3.40.0
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app_file: app.py
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pinned: false
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license: apache-2.0
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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version https://git-lfs.github.com/spec/v1
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oid sha256:826aceaffa9b514858b128b5478a9568e89ac9e596fe1c379cff219e9465b62d
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size 254
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app.py
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"""
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import argparse
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from collections import defaultdict
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from glob import glob
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import re
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import gradio as gr
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import pandas as pd
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questions = []
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question_selector_map = {}
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category_selector_map = defaultdict(list)
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def display_question(category_selector, request: gr.Request):
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# print(category_selector)
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choices = category_selector_map[category_selector]
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return gr.Dropdown.update(
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value=choices[0],
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choices=choices,
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)
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def display_pairwise_answer(
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question_selector, model_selector1, model_selector2, request: gr.Request
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):
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q = question_selector_map[question_selector]
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qid = q["question_id"]
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ans1 = q["conversation_a"]
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ans2 = q["conversation_b"]
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chat_mds = pairwise_to_gradio_chat_mds(q, ans1, ans2)
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return chat_mds
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newline_pattern1 = re.compile("\n\n(\d+\. )")
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newline_pattern2 = re.compile("\n\n(- )")
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def post_process_answer(x):
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"""Fix Markdown rendering problems."""
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x = x.replace("\u2022", "- ")
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x = re.sub(newline_pattern1, "\n\g<1>", x)
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x = re.sub(newline_pattern2, "\n\g<1>", x)
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return x
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def pairwise_to_gradio_chat_mds(question, ans_a, ans_b, turn=None):
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end = question["turn"] * 3
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mds = [""] * end
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base = 0
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for i in range(0, end, 3):
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mds[i] = "##### `User`\n" + question["conversation_a"][base]["content"].strip()
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mds[i + 1] = f"##### `{question['model_a']}`\n" + post_process_answer(
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ans_a[base + 1]["content"].strip()
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)
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mds[i + 2] = f"##### `{question['model_b']}`\n" + post_process_answer(
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ans_b[base + 1]["content"].strip()
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)
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base += 2
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winner = question["winner"] if "tie" in question["winner"] else question[question["winner"]]
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mds += [f"##### Vote: {winner}"]
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mds += [""] * (16 - len(mds))
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return mds
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def build_question_selector_map():
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global question_selector_map, category_selector_map
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# Build question selector map
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for q in questions:
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preview = q["conversation_a"][0]["content"][:128] + "..."
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question_selector_map[preview] = q
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category_selector_map[q["category"]].append(preview)
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def build_pairwise_browser_tab():
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global question_selector_map, category_selector_map
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num_sides = 2
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num_turns = 5
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side_names = ["A", "B"]
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question_selector_choices = list(question_selector_map.keys())
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category_selector_choices = list(category_selector_map.keys())
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print(category_selector_choices)
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# Selectors
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with gr.Row():
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with gr.Column(scale=1, min_width=200):
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category_selector = gr.Dropdown(
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choices=category_selector_choices,
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# value="Instruction Following",
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label="Category", container=False
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)
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with gr.Column(scale=100):
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question_selector = gr.Dropdown(
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choices=question_selector_choices, label="Question", container=False
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)
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# Conversation
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chat_mds = []
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for i in range(num_turns):
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chat_mds.append(gr.Markdown(elem_id=f"user_question_{i+1}"))
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with gr.Row():
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for j in range(num_sides):
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with gr.Column(scale=100):
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chat_mds.append(gr.Markdown())
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if j == 0:
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with gr.Column(scale=1, min_width=8):
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gr.Markdown()
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chat_mds.append(gr.Markdown())
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# Callbacks
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category_selector.change(display_question, [category_selector], [question_selector])
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question_selector.change(
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display_pairwise_answer,
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[question_selector],
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chat_mds,
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)
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return (category_selector,)
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def load_demo():
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dropdown_update = gr.Dropdown.update(value="Math")
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return dropdown_update
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def build_demo():
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build_question_selector_map()
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with gr.Blocks(
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title="Chatbot Arena Samples",
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theme=gr.themes.Base(text_size=gr.themes.sizes.text_lg),
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) as demo:
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gr.Markdown(
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"""
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# Chatbot Arena Samples
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We randomly sample 20 battles from each category using seed 42.
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| [Paper](https://arxiv.org/abs/2403.04132) | [Leaderboard](https://huggingface.co/spaces/lmsys/chatbot-arena-leaderboard) |
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"""
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)
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(category_selector,) = build_pairwise_browser_tab()
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demo.load(load_demo, [], [category_selector])
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return demo
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def load_questions(directory: str):
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import json
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"""Load questions from a file."""
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questions = []
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for file in glob(directory):
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with open(file, "r") as ques_file:
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for line in ques_file:
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if line:
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questions.append(json.loads(line))
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return questions
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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parser.add_argument("--host", type=str, default="0.0.0.0")
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parser.add_argument("--port", type=int)
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parser.add_argument("--share", action="store_true")
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args = parser.parse_args()
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print(args)
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questions = load_questions("data/*.jsonl")
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demo = build_demo()
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demo.launch(
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server_name=args.host, server_port=args.port, share=args.share, max_threads=200
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)
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version https://git-lfs.github.com/spec/v1
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oid sha256:6be9db2a4da8b10357d2cf03690e57af8c49b49620bc452325d94a8b3d134ce4
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size 5183
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data/sample_gpt-4o-mini.jsonl
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version https://git-lfs.github.com/spec/v1
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oid sha256:a66497ae13a735ef8acaa4a95c2bbcad16233f48637e3f4f57afff080d3ff529
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size 11210815
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data/sample_if.jsonl
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The diff for this file is too large to render.
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data/sample_math.jsonl
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The diff for this file is too large to render.
See raw diff
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