lmzheng commited on
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1 Parent(s): 72650c2

Update app.py

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  1. app.py +2 -3
app.py CHANGED
@@ -24,7 +24,7 @@ def make_leaderboard_md(elo_results):
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  - [MT-Bench](https://arxiv.org/abs/2306.05685) - a set of challenging multi-turn questions. We use GPT-4 to grade the model responses.
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  - [MMLU](https://arxiv.org/abs/2009.03300) (5-shot) - a test to measure a model's multitask accuracy on 57 tasks.
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- πŸ’» We use [fastchat.llm_judge](https://github.com/lm-sys/FastChat/tree/main/fastchat/llm_judge) to compute MT-bench scores (single-answer grading on a scale of 10) and win rates (against gpt-3.5). The Arena Elo ratings are computed by this [notebook]({notebook_url}). The MMLU scores are computed by [InstructEval](https://github.com/declare-lab/instruct-eval) and [Chain-of-Thought Hub](https://github.com/FranxYao/chain-of-thought-hub). Higher values are better for all benchmarks. Empty cells mean not available.
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  """
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  return leaderboard_md
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@@ -173,7 +173,6 @@ def build_leaderboard_tab(elo_results_file, leaderboard_table_file):
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  "Model",
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  "Arena Elo rating",
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  "MT-bench (score)",
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- "MT-bench (win rate %)",
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  "MMLU",
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  "License",
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  ]
@@ -191,7 +190,7 @@ def build_leaderboard_tab(elo_results_file, leaderboard_table_file):
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  gr.Dataframe(
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  headers=headers,
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- datatype=["markdown", "number", "number", "number", "number", "str"],
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  value=values,
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  elem_id="leaderboard_dataframe",
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  )
 
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  - [MT-Bench](https://arxiv.org/abs/2306.05685) - a set of challenging multi-turn questions. We use GPT-4 to grade the model responses.
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  - [MMLU](https://arxiv.org/abs/2009.03300) (5-shot) - a test to measure a model's multitask accuracy on 57 tasks.
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+ πŸ’» We use [fastchat.llm_judge](https://github.com/lm-sys/FastChat/tree/main/fastchat/llm_judge) to compute MT-bench scores (single-answer grading on a scale of 10). The Arena Elo ratings are computed by this [notebook]({notebook_url}). The MMLU scores are computed by [InstructEval](https://github.com/declare-lab/instruct-eval) and [Chain-of-Thought Hub](https://github.com/FranxYao/chain-of-thought-hub). Higher values are better for all benchmarks. Empty cells mean not available.
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  """
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  return leaderboard_md
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  "Model",
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  "Arena Elo rating",
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  "MT-bench (score)",
 
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  "MMLU",
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  "License",
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  ]
 
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  gr.Dataframe(
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  headers=headers,
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+ datatype=["markdown", "number", "number", "number", "str"],
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  value=values,
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  elem_id="leaderboard_dataframe",
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  )