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--- |
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license: apache-2.0 |
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model-index: |
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- name: Yi-1.5-34B-Chat-16K |
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results: |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: IFEval (0-Shot) |
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type: HuggingFaceH4/ifeval |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: inst_level_strict_acc and prompt_level_strict_acc |
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value: 45.64 |
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name: strict accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=01-ai/Yi-1.5-34B-Chat-16K |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: BBH (3-Shot) |
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type: BBH |
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args: |
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num_few_shot: 3 |
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metrics: |
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- type: acc_norm |
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value: 44.54 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=01-ai/Yi-1.5-34B-Chat-16K |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MATH Lvl 5 (4-Shot) |
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type: hendrycks/competition_math |
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args: |
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num_few_shot: 4 |
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metrics: |
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- type: exact_match |
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value: 18.81 |
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name: exact match |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=01-ai/Yi-1.5-34B-Chat-16K |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: GPQA (0-shot) |
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type: Idavidrein/gpqa |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: acc_norm |
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value: 11.74 |
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name: acc_norm |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=01-ai/Yi-1.5-34B-Chat-16K |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MuSR (0-shot) |
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type: TAUR-Lab/MuSR |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: acc_norm |
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value: 13.74 |
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name: acc_norm |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=01-ai/Yi-1.5-34B-Chat-16K |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MMLU-PRO (5-shot) |
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type: TIGER-Lab/MMLU-Pro |
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config: main |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 39.38 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=01-ai/Yi-1.5-34B-Chat-16K |
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name: Open LLM Leaderboard |
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--- |
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<div align="center"> |
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<picture> |
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<img src="https://raw.githubusercontent.com/01-ai/Yi/main/assets/img/Yi_logo_icon_light.svg" width="150px"> |
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</picture> |
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</div> |
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<p align="center"> |
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<a href="https://github.com/01-ai">🐙 GitHub</a> • |
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<a href="https://discord.gg/hYUwWddeAu">👾 Discord</a> • |
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<a href="https://twitter.com/01ai_yi">🐤 Twitter</a> • |
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<a href="https://github.com/01-ai/Yi-1.5/issues/2">💬 WeChat</a> |
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<br/> |
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<a href="https://arxiv.org/abs/2403.04652">📝 Paper</a> • |
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<a href="https://01-ai.github.io/">💪 Tech Blog</a> • |
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<a href="https://github.com/01-ai/Yi/tree/main?tab=readme-ov-file#faq">🙌 FAQ</a> • |
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<a href="https://github.com/01-ai/Yi/tree/main?tab=readme-ov-file#learning-hub">📗 Learning Hub</a> |
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</p> |
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# Intro |
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Yi-1.5 is an upgraded version of Yi. It is continuously pre-trained on Yi with a high-quality corpus of 500B tokens and fine-tuned on 3M diverse fine-tuning samples. |
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Compared with Yi, Yi-1.5 delivers stronger performance in coding, math, reasoning, and instruction-following capability, while still maintaining excellent capabilities in language understanding, commonsense reasoning, and reading comprehension. |
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<div align="center"> |
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Model | Context Length | Pre-trained Tokens |
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| :------------: | :------------: | :------------: | |
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| Yi-1.5 | 4K, 16K, 32K | 3.6T |
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</div> |
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# Models |
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- Chat models |
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<div align="center"> |
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| Name | Download | |
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| --------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------- | |
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| Yi-1.5-34B-Chat | • [🤗 Hugging Face](https://huggingface.co/collections/01-ai/yi-15-2024-05-663f3ecab5f815a3eaca7ca8) • [🤖 ModelScope](https://www.modelscope.cn/organization/01ai) • [🟣 wisemodel](https://wisemodel.cn/organization/01.AI)| |
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| Yi-1.5-34B-Chat-16K | • [🤗 Hugging Face](https://huggingface.co/collections/01-ai/yi-15-2024-05-663f3ecab5f815a3eaca7ca8) • [🤖 ModelScope](https://www.modelscope.cn/organization/01ai) • [🟣 wisemodel](https://wisemodel.cn/organization/01.AI) | |
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| Yi-1.5-9B-Chat | • [🤗 Hugging Face](https://huggingface.co/collections/01-ai/yi-15-2024-05-663f3ecab5f815a3eaca7ca8) • [🤖 ModelScope](https://www.modelscope.cn/organization/01ai) • [🟣 wisemodel](https://wisemodel.cn/organization/01.AI) | |
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| Yi-1.5-9B-Chat-16K | • [🤗 Hugging Face](https://huggingface.co/collections/01-ai/yi-15-2024-05-663f3ecab5f815a3eaca7ca8) • [🤖 ModelScope](https://www.modelscope.cn/organization/01ai) • [🟣 wisemodel](https://wisemodel.cn/organization/01.AI) | |
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| Yi-1.5-6B-Chat | • [🤗 Hugging Face](https://huggingface.co/collections/01-ai/yi-15-2024-05-663f3ecab5f815a3eaca7ca8) • [🤖 ModelScope](https://www.modelscope.cn/organization/01ai) • [🟣 wisemodel](https://wisemodel.cn/organization/01.AI) | |
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</div> |
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- Base models |
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<div align="center"> |
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| Name | Download | |
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| ---------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------- | |
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| Yi-1.5-34B | • [🤗 Hugging Face](https://huggingface.co/collections/01-ai/yi-15-2024-05-663f3ecab5f815a3eaca7ca8) • [🤖 ModelScope](https://www.modelscope.cn/organization/01ai) • [🟣 wisemodel](https://wisemodel.cn/organization/01.AI) | |
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| Yi-1.5-34B-32K | • [🤗 Hugging Face](https://huggingface.co/collections/01-ai/yi-15-2024-05-663f3ecab5f815a3eaca7ca8) • [🤖 ModelScope](https://www.modelscope.cn/organization/01ai) • [🟣 wisemodel](https://wisemodel.cn/organization/01.AI) | |
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| Yi-1.5-9B | • [🤗 Hugging Face](https://huggingface.co/collections/01-ai/yi-15-2024-05-663f3ecab5f815a3eaca7ca8) • [🤖 ModelScope](https://www.modelscope.cn/organization/01ai) • [🟣 wisemodel](https://wisemodel.cn/organization/01.AI) | |
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| Yi-1.5-9B-32K | • [🤗 Hugging Face](https://huggingface.co/collections/01-ai/yi-15-2024-05-663f3ecab5f815a3eaca7ca8) • [🤖 ModelScope](https://www.modelscope.cn/organization/01ai) • [🟣 wisemodel](https://wisemodel.cn/organization/01.AI) | |
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| Yi-1.5-6B | • [🤗 Hugging Face](https://huggingface.co/collections/01-ai/yi-15-2024-05-663f3ecab5f815a3eaca7ca8) • [🤖 ModelScope](https://www.modelscope.cn/organization/01ai) • [🟣 wisemodel](https://wisemodel.cn/organization/01.AI) | |
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</div> |
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# Benchmarks |
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- Chat models |
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Yi-1.5-34B-Chat is on par with or excels beyond larger models in most benchmarks. |
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Yi-1.5-9B-Chat is the top performer among similarly sized open-source models. |
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- Base models |
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Yi-1.5-34B is on par with or excels beyond larger models in some benchmarks. |
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Yi-1.5-9B is the top performer among similarly sized open-source models. |
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# Quick Start |
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For getting up and running with Yi-1.5 models quickly, see [README](https://github.com/01-ai/Yi-1.5). |
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) |
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_01-ai__Yi-1.5-34B-Chat-16K) |
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| Metric |Value| |
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|-------------------|----:| |
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|Avg. |28.98| |
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|IFEval (0-Shot) |45.64| |
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|BBH (3-Shot) |44.54| |
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|MATH Lvl 5 (4-Shot)|18.81| |
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|GPQA (0-shot) |11.74| |
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|MuSR (0-shot) |13.74| |
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|MMLU-PRO (5-shot) |39.38| |
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