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**Original model**: [Qwen2.5-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-32B-Instruct)<br>
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**GGUF quantization:** provided by [bartowski](https://huggingface.co/bartowski) based on `llama.cpp` release [b3772](https://github.com/ggerganov/llama.cpp/releases/tag/b3772)<br>
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## Special thanks
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🙏 Special thanks to [Georgi Gerganov](https://github.com/ggerganov) and the whole team working on [llama.cpp](https://github.com/ggerganov/llama.cpp/) for making all of this possible.
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**Original model**: [Qwen2.5-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-32B-Instruct)<br>
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**GGUF quantization:** provided by [bartowski](https://huggingface.co/bartowski) based on `llama.cpp` release [b3772](https://github.com/ggerganov/llama.cpp/releases/tag/b3772)<br>
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## Technical Details
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Long context: Support for 128k tokens and 8k token generation
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Large-scale training dataset: Encompasses a huge range of knowledge.
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Enhanced structured data understanding and generation.
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Over 29 languages including Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, Korean, Vietnamese, Thai, and Arabic.
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More details available [here](https://qwenlm.github.io/blog/qwen2.5/)
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## Special thanks
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🙏 Special thanks to [Georgi Gerganov](https://github.com/ggerganov) and the whole team working on [llama.cpp](https://github.com/ggerganov/llama.cpp/) for making all of this possible.
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