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import pandas as pd |
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df = pd.read_csv("data/raw_scores.csv") |
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COLS = df.columns.to_list() |
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df.insert(len(COLS), "models_query", df["Models"]) |
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df.insert(2, "Average score", df.iloc[:, 5:-3].mean(axis=1).round(2)) |
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old_size = len(df.columns) |
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for col in df.columns[6:-2]: |
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df[col + " rank"] = df[col].rank(ascending=False) |
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df[col + " rank"] = len(df) - (df[col + " rank"] - 1) |
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df["Win Rate"] = df.iloc[:, old_size:].mean(axis=1).round(2) |
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df = df.drop(df.columns[old_size:-1], axis=1) |
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df = df[["Models", "Size (B)", "Win Rate"] + df.columns[2:-1].tolist()] |
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df = df.sort_values(by=["Win Rate"], ascending=False) |
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links = { |
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"WizardCoder-15B-V1.0": "https://huggingface.co/WizardLM/WizardCoder-15B-V1.0", |
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"NewHope-13B": "https://huggingface.co/SLAM-group/NewHope", |
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"StarCoder-15B": "https://huggingface.co/bigcode/starcoder", |
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"StarCoderBase-15B": "https://huggingface.co/bigcode/starcoderbase", |
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"StarCoderBase-7B": "https://huggingface.co/bigcode/starcoderbase-7b", |
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"StarCoderBase-3B": "https://huggingface.co/bigcode/starcoderbase-3b", |
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"StarCoderBase-1.1B": "https://huggingface.co/bigcode/starcoderbase-1b", |
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"SantaCoder-1.1B": "https://huggingface.co/bigcode/santacoder", |
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"Replit-2.7B": "https://huggingface.co/replit/replit-code-v1-3b", |
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"CodeGeex2-6B": "https://huggingface.co/THUDM/codegeex2-6b", |
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"CodeGen25-7B-multi": "https://huggingface.co/Salesforce/codegen25-7b-multi", |
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"CodeGen25-7B-mono": "https://huggingface.co/Salesforce/codegen25-7b-mono", |
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"CodeGen-16B-Multi": "https://huggingface.co/Salesforce/codegen-16B-multi", |
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} |
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df["Links"] = df["Models"].map(links) |
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df.insert(0, "T", "🟢") |
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df.loc[(df["Models"].str.contains("WizardCoder") | df["Models"].str.contains("NewHope")), "T"] = "🔶" |
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df.to_csv("data/code_eval_board.csv", index=False) |
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