yi-01-ai
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README.md
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</details>
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## Model Performance
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### Base Model Performance
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For more detailed explanation, please read the [doc](https://github.com/01-ai/Yi/tree/main/quantization/awq)
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## Ecosystem
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🤗 You are encouraged to create a PR and share your awesome work built on top of
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the Yi series models.
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- Serving
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- [ScaleLLM](https://github.com/vectorch-ai/ScaleLLM#supported-models): Efficiently run Yi models locally.
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- Quantization
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- [TheBloke/Yi-34B-GGUF](https://huggingface.co/TheBloke/Yi-34B-GGUF)
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- [TheBloke/Yi-34B-GPTQ](https://huggingface.co/TheBloke/Yi-34B-GPTQ)
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- Finetuning
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- [NousResearch/Nous-Capybara-34B](https://huggingface.co/NousResearch/Nous-Capybara-34B)
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## FAQ
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1. **What dataset was this trained with?**
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</details>
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## Ecosystem
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🤗 You are encouraged to create a PR and share your awesome work built on top of
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the Yi series models.
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- Serving
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- [ScaleLLM](https://github.com/vectorch-ai/ScaleLLM#supported-models): Efficiently run Yi models locally.
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- Quantization
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- [TheBloke/Yi-34B-GGUF](https://huggingface.co/TheBloke/Yi-34B-GGUF)
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- [TheBloke/Yi-34B-GPTQ](https://huggingface.co/TheBloke/Yi-34B-GPTQ)
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- Finetuning
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- [NousResearch/Nous-Capybara-34B](https://huggingface.co/NousResearch/Nous-Capybara-34B)
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- [SUSTech/SUS-Chat-34B](https://huggingface.co/SUSTech/SUS-Chat-34B): This
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model ranks first among all models below 70B and has outperformed the twice
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larger
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[deepseek-llm-67b-chat](https://huggingface.co/deepseek-ai/deepseek-llm-67b-chat).
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You can check the result in [🤗 Open LLM
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Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
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## Model Performance
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### Base Model Performance
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For more detailed explanation, please read the [doc](https://github.com/01-ai/Yi/tree/main/quantization/awq)
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## FAQ
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1. **What dataset was this trained with?**
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