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import json |
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import gradio as gr |
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from huggingface_hub import HfFileSystem |
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RESULTS_DATASET_ID = "datasets/open-llm-leaderboard/results" |
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fs = HfFileSystem() |
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def fetch_result_paths(): |
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paths = fs.glob(f"{RESULTS_DATASET_ID}/**/**/*.json") |
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return paths |
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def filter_latest_result_path_per_model(paths): |
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from collections import defaultdict |
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d = defaultdict(list) |
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for path in paths: |
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model_id, _ = path[len(RESULTS_DATASET_ID) +1:].rsplit("/", 1) |
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d[model_id].append(path) |
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return {model_id: max(paths) for model_id, paths in d.items()} |
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def get_result_path_from_model(model_id, result_path_per_model): |
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return result_path_per_model[model_id] |
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def load_result(result_path) -> dict: |
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with fs.open(result_path, "r") as f: |
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data = json.load(f) |
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return data |
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def render_result(model_id): |
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result_path = get_result_path_from_model(model_id, latest_result_path_per_model) |
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return load_result(result_path) |
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latest_result_path_per_model = filter_latest_result_path_per_model(fetch_result_paths()) |
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with gr.Blocks() as demo: |
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gr.HTML("<h1 style='text-align: center;'>Results of the 🤗 Open LLM Leaderboard</h1>") |
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gr.HTML("<h3 style='text-align: center;'>Select a result to load</h3>") |
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model_id = gr.Dropdown(choices=list(latest_result_path_per_model.keys()), label="Results") |
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load_btn = gr.Button("Load") |
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result = gr.JSON(label="Result") |
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load_btn.click( |
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fn=render_result, |
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inputs=model_id, |
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outputs=result, |
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) |
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demo.launch() |
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