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# Llama.cpp imatrix quantizations of meta-llama/Meta-Llama-3.1-70B-Instruct
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Using llama.cpp commit [b5e9546](https://github.com/ggerganov/llama.cpp/commit/b5e95468b1676e1e5c9d80d1eeeb26f542a38f42) for quantization, featuring llama 3.1 rope scaling factors. This fixes low-quality issues when using 8-128k context lengths.
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Original model: [https://huggingface.co/meta-llama/Meta-Llama-3.1-70B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-70B-Instruct)
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# Llama.cpp imatrix quantizations of meta-llama/Meta-Llama-3.1-70B-Instruct
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<!-- Better pic but I would like to talk about my quants on Linkedin so yeah <img src="https://cdn-uploads.huggingface.co/production/uploads/646410e04bf9122922289dc7/xlkSJli8IQ9KoTAuTKOF2.png" alt="llama" width="30%"/> -->
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<img src="https://cdn-uploads.huggingface.co/production/uploads/646410e04bf9122922289dc7/LQUL7YII8okA8CG54mQSI.jpeg" alt="llama" width="60%"/>
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Using llama.cpp commit [b5e9546](https://github.com/ggerganov/llama.cpp/commit/b5e95468b1676e1e5c9d80d1eeeb26f542a38f42) for quantization, featuring llama 3.1 rope scaling factors. This fixes low-quality issues when using 8-128k context lengths.
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Original model: [https://huggingface.co/meta-llama/Meta-Llama-3.1-70B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-70B-Instruct)
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