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Parent(s):
c0dd25e
Add column for commercial use + logic in streamlit app + disclaimer
Browse files- README.md +42 -38
- streamlit_app.py +20 -5
README.md
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@@ -20,43 +20,43 @@ We are always happy for contributions! You can contribute by the following:
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## Leaderboard
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| Model Name | Chatbot Arena Elo | HumanEval-Python (pass@1) | LAMBADA (zero-shot) | MMLU (zero-shot) | TriviaQA (zero-shot) |
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| -------------------------------------------------------------------------------------- | ------------------------------------------------ | ------------------------------------------------------------------------------ | --------------------------------------------- | ---------------- | --------------------------------------------- |
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| [alpaca-13b](https://crfm.stanford.edu/2023/03/13/alpaca.html) | [1008](https://lmsys.org/blog/2023-05-03-arena/) | | | | |
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| [cerebras-gpt-7b](https://huggingface.co/cerebras/Cerebras-GPT-6.7B) | | | [0.636](https://www.mosaicml.com/blog/mpt-7b) | 0.259 | [0.141](https://www.mosaicml.com/blog/mpt-7b) |
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| [cerebras-gpt-13b](https://huggingface.co/cerebras/Cerebras-GPT-13B) | | | [0.635](https://www.mosaicml.com/blog/mpt-7b) | 0.258 | [0.146](https://www.mosaicml.com/blog/mpt-7b) |
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| [chatglm-6b](https://chatglm.cn/blog) | [985](https://lmsys.org/blog/2023-05-03-arena/) | | | | |
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| [chinchilla-70b](https://arxiv.org/abs/2203.15556v1) | | | [0.774](https://arxiv.org/abs/2203.15556v1) | | |
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| [code-cushman-001](https://arxiv.org/abs/2107.03374) | | [33.5](https://drive.google.com/file/d/1cN-b9GnWtHzQRoE7M7gAEyivY0kl4BYs/view) | | | |
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| [code-davinci-002](https://arxiv.org/abs/2207.10397v2) | | [65.8](https://arxiv.org/abs/2207.10397v2) | | | |
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| [codegen-16B-mono](https://huggingface.co/Salesforce/codegen-16B-mono) | | [29.3](https://drive.google.com/file/d/1cN-b9GnWtHzQRoE7M7gAEyivY0kl4BYs/view) | | | |
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| [codegen-16B-multi](https://huggingface.co/Salesforce/codegen-16B-multi) | | [18.3](https://drive.google.com/file/d/1cN-b9GnWtHzQRoE7M7gAEyivY0kl4BYs/view) | | | |
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| [codegx-13b](http://keg.cs.tsinghua.edu.cn/codegeex/) | | [22.9](https://drive.google.com/file/d/1cN-b9GnWtHzQRoE7M7gAEyivY0kl4BYs/view) | | | |
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| [codex-12b](https://arxiv.org/abs/2107.03374v2) | | [28.81](https://arxiv.org/abs/2107.03374v2) | | | |
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| [dolly-v2-12b](https://huggingface.co/databricks/dolly-v2-12b) | [944](https://lmsys.org/blog/2023-05-03-arena/) | | | | |
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| [eleuther-pythia-7b](https://huggingface.co/EleutherAI/pythia-6.9b) | | | [0.667](https://www.mosaicml.com/blog/mpt-7b) | 0.265 | [0.198](https://www.mosaicml.com/blog/mpt-7b) |
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| [eleuther-pythia-12b](https://huggingface.co/EleutherAI/pythia-12b) | | | [0.704](https://www.mosaicml.com/blog/mpt-7b) | 0.253 | [0.233](https://www.mosaicml.com/blog/mpt-7b) |
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| [fastchat-t5-3b](https://huggingface.co/lmsys/fastchat-t5-3b-v1.0) | [951](https://lmsys.org/blog/2023-05-03-arena/) | | | | |
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| [gpt-3.5-175b](https://arxiv.org/abs/2303.08774v3) | | [48.1](https://arxiv.org/abs/2303.08774v3) | [0.762](https://arxiv.org/abs/2303.08774v3) | | |
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| [gpt-4](https://arxiv.org/abs/2303.08774v3) | | [67.0](https://arxiv.org/abs/2303.08774v3) | | | |
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| [gpt-neox-20b](https://huggingface.co/EleutherAI/gpt-neox-20b) | | | [0.719](https://www.mosaicml.com/blog/mpt-7b) | 0.269 | [0.347](https://www.mosaicml.com/blog/mpt-7b) |
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| [koala-13b](https://bair.berkeley.edu/blog/2023/04/03/koala/) | [1082](https://lmsys.org/blog/2023-05-03-arena/) | | | | |
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| [llama-7b](https://arxiv.org/abs/2302.13971) | | [10.5](https://drive.google.com/file/d/1cN-b9GnWtHzQRoE7M7gAEyivY0kl4BYs/view) | [0.738](https://www.mosaicml.com/blog/mpt-7b) | 0.302 | [0.443](https://www.mosaicml.com/blog/mpt-7b) |
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| [llama-13b](https://arxiv.org/abs/2302.13971) | [932](https://lmsys.org/blog/2023-05-03-arena/) | [15.8](https://drive.google.com/file/d/1cN-b9GnWtHzQRoE7M7gAEyivY0kl4BYs/view) | | | |
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| [llama-33b](https://arxiv.org/abs/2302.13971) | | [21.7](https://drive.google.com/file/d/1cN-b9GnWtHzQRoE7M7gAEyivY0kl4BYs/view) | | | |
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| [llama-65b](https://arxiv.org/abs/2302.13971) | | [23.7](https://drive.google.com/file/d/1cN-b9GnWtHzQRoE7M7gAEyivY0kl4BYs/view) | | | |
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| [mpt-7b](https://huggingface.co/mosaicml/mpt-7b) | | | [0.702](https://www.mosaicml.com/blog/mpt-7b) | 0.296 | [0.343](https://www.mosaicml.com/blog/mpt-7b) |
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| [oasst-pythia-12b](https://huggingface.co/OpenAssistant/pythia-12b-pre-v8-12.5k-steps) | [1065](https://lmsys.org/blog/2023-05-03-arena/) | | | | |
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| [opt-7b](https://huggingface.co/facebook/opt-6.7b) | | | [0.677](https://www.mosaicml.com/blog/mpt-7b) | 0.251 | [0.227](https://www.mosaicml.com/blog/mpt-7b) |
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| [opt-13b](https://huggingface.co/facebook/opt-13b) | | | [0.692](https://www.mosaicml.com/blog/mpt-7b) | 0.257 | [0.282](https://www.mosaicml.com/blog/mpt-7b) |
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| [palm-540b](https://arxiv.org/abs/2204.02311v5) | | [26.2](https://drive.google.com/file/d/1cN-b9GnWtHzQRoE7M7gAEyivY0kl4BYs/view) | [0.779](https://arxiv.org/abs/2204.02311v5) | | |
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| [stablelm-base-alpha-7b](https://huggingface.co/stabilityai/stablelm-base-alpha-7b) | | | [0.533](https://www.mosaicml.com/blog/mpt-7b) | 0.251 | [0.049](https://www.mosaicml.com/blog/mpt-7b) |
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| [stablelm-tuned-alpha-7b](https://huggingface.co/stabilityai/stablelm-tuned-alpha-7b) | [858](https://lmsys.org/blog/2023-05-03-arena/) | | | | |
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| [starcoder-base-16B](https://huggingface.co/bigcode/starcoderbase) | | [30.4](https://drive.google.com/file/d/1cN-b9GnWtHzQRoE7M7gAEyivY0kl4BYs/view) | | | |
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| [starcoder-16B](https://huggingface.co/bigcode/starcoder) | | [33.6](https://drive.google.com/file/d/1cN-b9GnWtHzQRoE7M7gAEyivY0kl4BYs/view) | | | |
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| [starcoder-16B (prompted)](https://huggingface.co/bigcode/starcoder) | | [40.8](https://drive.google.com/file/d/1cN-b9GnWtHzQRoE7M7gAEyivY0kl4BYs/view) | | | |
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| [vicuna-13b](https://huggingface.co/lmsys/vicuna-13b-delta-v0) | [1169](https://lmsys.org/blog/2023-05-03-arena/) | | | | |
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## Benchmarks
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## Sources
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The results of this leaderboard are collected from the individual papers and published results of the model authors. For each reported value, the source is added as a link.
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## Leaderboard
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| Model Name | Commercial Use? | Chatbot Arena Elo | HumanEval-Python (pass@1) | LAMBADA (zero-shot) | MMLU (zero-shot) | TriviaQA (zero-shot) |
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| -------------------------------------------------------------------------------------- | --------------- | ------------------------------------------------ | ------------------------------------------------------------------------------ | --------------------------------------------- | ---------------- | --------------------------------------------- |
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| [alpaca-13b](https://crfm.stanford.edu/2023/03/13/alpaca.html) | no | [1008](https://lmsys.org/blog/2023-05-03-arena/) | | | | |
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| [cerebras-gpt-7b](https://huggingface.co/cerebras/Cerebras-GPT-6.7B) | yes | | | [0.636](https://www.mosaicml.com/blog/mpt-7b) | 0.259 | [0.141](https://www.mosaicml.com/blog/mpt-7b) |
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| [cerebras-gpt-13b](https://huggingface.co/cerebras/Cerebras-GPT-13B) | yes | | | [0.635](https://www.mosaicml.com/blog/mpt-7b) | 0.258 | [0.146](https://www.mosaicml.com/blog/mpt-7b) |
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| [chatglm-6b](https://chatglm.cn/blog) | yes | [985](https://lmsys.org/blog/2023-05-03-arena/) | | | | |
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| [chinchilla-70b](https://arxiv.org/abs/2203.15556v1) | no | | | [0.774](https://arxiv.org/abs/2203.15556v1) | | |
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| [code-cushman-001](https://arxiv.org/abs/2107.03374) | no | | [33.5](https://drive.google.com/file/d/1cN-b9GnWtHzQRoE7M7gAEyivY0kl4BYs/view) | | | |
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| [code-davinci-002](https://arxiv.org/abs/2207.10397v2) | yes | | [65.8](https://arxiv.org/abs/2207.10397v2) | | | |
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| [codegen-16B-mono](https://huggingface.co/Salesforce/codegen-16B-mono) | yes | | [29.3](https://drive.google.com/file/d/1cN-b9GnWtHzQRoE7M7gAEyivY0kl4BYs/view) | | | |
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| [codegen-16B-multi](https://huggingface.co/Salesforce/codegen-16B-multi) | yes | | [18.3](https://drive.google.com/file/d/1cN-b9GnWtHzQRoE7M7gAEyivY0kl4BYs/view) | | | |
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| [codegx-13b](http://keg.cs.tsinghua.edu.cn/codegeex/) | no | | [22.9](https://drive.google.com/file/d/1cN-b9GnWtHzQRoE7M7gAEyivY0kl4BYs/view) | | | |
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| [codex-12b](https://arxiv.org/abs/2107.03374v2) | no | | [28.81](https://arxiv.org/abs/2107.03374v2) | | | |
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| [dolly-v2-12b](https://huggingface.co/databricks/dolly-v2-12b) | yes | [944](https://lmsys.org/blog/2023-05-03-arena/) | | | | |
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| [eleuther-pythia-7b](https://huggingface.co/EleutherAI/pythia-6.9b) | yes | | | [0.667](https://www.mosaicml.com/blog/mpt-7b) | 0.265 | [0.198](https://www.mosaicml.com/blog/mpt-7b) |
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| [eleuther-pythia-12b](https://huggingface.co/EleutherAI/pythia-12b) | yes | | | [0.704](https://www.mosaicml.com/blog/mpt-7b) | 0.253 | [0.233](https://www.mosaicml.com/blog/mpt-7b) |
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| [fastchat-t5-3b](https://huggingface.co/lmsys/fastchat-t5-3b-v1.0) | yes | [951](https://lmsys.org/blog/2023-05-03-arena/) | | | | |
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| [gpt-3.5-175b](https://arxiv.org/abs/2303.08774v3) | yes | | [48.1](https://arxiv.org/abs/2303.08774v3) | [0.762](https://arxiv.org/abs/2303.08774v3) | | |
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| [gpt-4](https://arxiv.org/abs/2303.08774v3) | yes | | [67.0](https://arxiv.org/abs/2303.08774v3) | | | |
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| [gpt-neox-20b](https://huggingface.co/EleutherAI/gpt-neox-20b) | yes | | | [0.719](https://www.mosaicml.com/blog/mpt-7b) | 0.269 | [0.347](https://www.mosaicml.com/blog/mpt-7b) |
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| [gpt-j-6b](https://huggingface.co/EleutherAI/gpt-j-6b) | yes | | | [0.683](https://www.mosaicml.com/blog/mpt-7b) | 0.261 | [0.234](https://www.mosaicml.com/blog/mpt-7b) |
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| [koala-13b](https://bair.berkeley.edu/blog/2023/04/03/koala/) | no | [1082](https://lmsys.org/blog/2023-05-03-arena/) | | | | |
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| [llama-7b](https://arxiv.org/abs/2302.13971) | no | | [10.5](https://drive.google.com/file/d/1cN-b9GnWtHzQRoE7M7gAEyivY0kl4BYs/view) | [0.738](https://www.mosaicml.com/blog/mpt-7b) | 0.302 | [0.443](https://www.mosaicml.com/blog/mpt-7b) |
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| [llama-13b](https://arxiv.org/abs/2302.13971) | no | [932](https://lmsys.org/blog/2023-05-03-arena/) | [15.8](https://drive.google.com/file/d/1cN-b9GnWtHzQRoE7M7gAEyivY0kl4BYs/view) | | | |
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| [llama-33b](https://arxiv.org/abs/2302.13971) | no | | [21.7](https://drive.google.com/file/d/1cN-b9GnWtHzQRoE7M7gAEyivY0kl4BYs/view) | | | |
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| [llama-65b](https://arxiv.org/abs/2302.13971) | no | | [23.7](https://drive.google.com/file/d/1cN-b9GnWtHzQRoE7M7gAEyivY0kl4BYs/view) | | | |
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| [mpt-7b](https://huggingface.co/mosaicml/mpt-7b) | yes | | | [0.702](https://www.mosaicml.com/blog/mpt-7b) | 0.296 | [0.343](https://www.mosaicml.com/blog/mpt-7b) |
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| [oasst-pythia-12b](https://huggingface.co/OpenAssistant/pythia-12b-pre-v8-12.5k-steps) | yes | [1065](https://lmsys.org/blog/2023-05-03-arena/) | | | | |
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| [opt-7b](https://huggingface.co/facebook/opt-6.7b) | no | | | [0.677](https://www.mosaicml.com/blog/mpt-7b) | 0.251 | [0.227](https://www.mosaicml.com/blog/mpt-7b) |
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| [opt-13b](https://huggingface.co/facebook/opt-13b) | no | | | [0.692](https://www.mosaicml.com/blog/mpt-7b) | 0.257 | [0.282](https://www.mosaicml.com/blog/mpt-7b) |
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| [palm-540b](https://arxiv.org/abs/2204.02311v5) | no | | [26.2](https://drive.google.com/file/d/1cN-b9GnWtHzQRoE7M7gAEyivY0kl4BYs/view) | [0.779](https://arxiv.org/abs/2204.02311v5) | | |
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| [stablelm-base-alpha-7b](https://huggingface.co/stabilityai/stablelm-base-alpha-7b) | yes | | | [0.533](https://www.mosaicml.com/blog/mpt-7b) | 0.251 | [0.049](https://www.mosaicml.com/blog/mpt-7b) |
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| [stablelm-tuned-alpha-7b](https://huggingface.co/stabilityai/stablelm-tuned-alpha-7b) | no | [858](https://lmsys.org/blog/2023-05-03-arena/) | | | | |
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| [starcoder-base-16B](https://huggingface.co/bigcode/starcoderbase) | yes | | [30.4](https://drive.google.com/file/d/1cN-b9GnWtHzQRoE7M7gAEyivY0kl4BYs/view) | | | |
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| [starcoder-16B](https://huggingface.co/bigcode/starcoder) | yes | | [33.6](https://drive.google.com/file/d/1cN-b9GnWtHzQRoE7M7gAEyivY0kl4BYs/view) | | | |
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| [starcoder-16B (prompted)](https://huggingface.co/bigcode/starcoder) | yes | | [40.8](https://drive.google.com/file/d/1cN-b9GnWtHzQRoE7M7gAEyivY0kl4BYs/view) | | | |
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| [vicuna-13b](https://huggingface.co/lmsys/vicuna-13b-delta-v0) | no | [1169](https://lmsys.org/blog/2023-05-03-arena/) | | | | |
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## Benchmarks
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## Sources
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The results of this leaderboard are collected from the individual papers and published results of the model authors. For each reported value, the source is added as a link.
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## Disclaimer
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Above information may be wrong. If you want to use a published model for commercial use, please contact a lawyer.
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streamlit_app.py
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.dropna(axis=1, how="all") # drop empty columns
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.iloc[1:] # drop first row which is the "----" separator of the original markdown table
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.sort_index(ascending=True)
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.astype(float, errors="ignore")
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)
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return text
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def filter_dataframe(df: pd.DataFrame) -> pd.DataFrame:
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"""
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Adds a UI on top of a dataframe to let viewers filter columns
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Args:
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df (pd.DataFrame): Original dataframe
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Returns:
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pd.DataFrame: Filtered dataframe
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df = df.copy()
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modification_container = st.container()
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with modification_container:
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if to_filter_index:
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df = pd.DataFrame(df.loc[to_filter_index])
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to_filter_columns = st.multiselect("Filter by benchmark:", df.columns)
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if to_filter_columns:
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return df
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leaderboard_table = extract_markdown_table_from_multiline(readme, table_headline="## Leaderboard")
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leaderboard_table = remove_markdown_links(leaderboard_table)
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df_leaderboard = extract_table_and_format_from_markdown_text(leaderboard_table)
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st.markdown("## Leaderboard")
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st.dataframe(filter_dataframe(df_leaderboard))
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def setup_benchmarks(readme: str):
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def setup_footer():
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st.markdown(
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"""
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@@ -186,6 +200,7 @@ def main():
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setup_leaderboard(readme)
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setup_benchmarks(readme)
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setup_sources()
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setup_footer()
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.dropna(axis=1, how="all") # drop empty columns
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.iloc[1:] # drop first row which is the "----" separator of the original markdown table
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.sort_index(ascending=True)
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.apply(lambda x: x.str.strip() if x.dtype == "object" else x)
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.replace("", float("NaN"))
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.astype(float, errors="ignore")
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)
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return text
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def filter_dataframe(df: pd.DataFrame, ignore_columns: list[str] | None = None) -> pd.DataFrame:
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"""
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Adds a UI on top of a dataframe to let viewers filter columns
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Args:
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df (pd.DataFrame): Original dataframe
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ignore_columns (list[str], optional): Columns to ignore. Defaults to None.
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Returns:
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pd.DataFrame: Filtered dataframe
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df = df.copy()
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if ignore_columns is None:
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ignore_columns = []
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modification_container = st.container()
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with modification_container:
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if to_filter_index:
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df = pd.DataFrame(df.loc[to_filter_index])
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to_filter_columns = st.multiselect("Filter by benchmark:", [c for c in df.columns if c not in ignore_columns])
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if to_filter_columns:
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df = pd.DataFrame(df[ignore_columns + to_filter_columns])
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return df
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leaderboard_table = extract_markdown_table_from_multiline(readme, table_headline="## Leaderboard")
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leaderboard_table = remove_markdown_links(leaderboard_table)
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df_leaderboard = extract_table_and_format_from_markdown_text(leaderboard_table)
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df_leaderboard["Commercial Use?"] = df_leaderboard["Commercial Use?"].map({"yes": 1, "no": 0}).astype(bool)
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st.markdown("## Leaderboard")
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st.dataframe(filter_dataframe(df_leaderboard, ignore_columns=["Commercial Use?"]))
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def setup_benchmarks(readme: str):
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)
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def setup_disclaimer():
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st.markdown("## Disclaimer")
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st.markdown(
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"Above information may be wrong. If you want to use a published model for commercial use, please contact a "
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"lawyer."
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)
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def setup_footer():
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st.markdown(
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"""
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setup_leaderboard(readme)
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setup_benchmarks(readme)
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setup_sources()
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setup_disclaimer()
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setup_footer()
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