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Update app.py
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app.py
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@@ -87,20 +87,24 @@ def make_df(file_path: str, n_rows: int) -> pd.DataFrame:
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"""
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columns = ["Available on the hub", "Model sha", "T", "Type", "Precision",
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"Architecture", "Weight type", "Hub ❤️", "Flagged", "MoE"]
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ds = pd.read_csv(
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df = (
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ds[
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(ds["#Params (B)"] == 8
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(ds["
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(ds["
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(ds["
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(ds["
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]
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.drop(columns=columns)
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.drop_duplicates(subset=["Model"])
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.iloc[:n_rows]
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)
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print(df)
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return df
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"""
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columns = ["Available on the hub", "Model sha", "T", "Type", "Precision",
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"Architecture", "Weight type", "Hub ❤️", "Flagged", "MoE"]
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ds = pd.read_csv("open-llm-leaderboard.csv", encoding='utf-8')
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df = (
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ds[
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(ds["#Params (B)"] == 8)
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& (ds["Architecture"] == "LlamaForCausalLM")
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& (ds["Available on the hub"] == True)
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& (ds["Flagged"] == True)
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& (~ds["Model"].str.lower().str.contains("yi"))
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& (~ds["Model"].str.lower().str.contains("9b"))
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& (~ds["Model"].str.lower().str.contains("8xqmff94/slm"))
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& (ds["MoE"] == True)
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& (ds["Weight type"] == "Original")
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]
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.drop(columns=columns)
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.drop_duplicates(subset=["Model"])
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.sort_values(by="MMLU", ascending=False)
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.iloc[:n_rows]
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)
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return df
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