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  <img src="https://i.imgur.com/P68dXux.png" width="400"/>
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  # Meta-Llama-3.1-8B-Claude-iMat-GGUF
 
 
 
 
 
 
 
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  Quantized from Meta-Llama-3.1-8B-Claude fp16
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  * Weighted quantizations were creating using fp16 GGUF and groups_merged.txt in 88 chunks and n_ctx=512
 
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  <img src="https://i.imgur.com/P68dXux.png" width="400"/>
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  # Meta-Llama-3.1-8B-Claude-iMat-GGUF
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+ >[!TIP]
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+ ><h2>7/28 Update:</h2>
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+ >
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+ >* Reconverted using llama.cpp [b3479](https://github.com/ggerganov/llama.cpp/releases?page=1), adds llama 3.1 rope scaling factors to llama conversion and inference, improving results for context windows above 8192
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+ >* Importance matrix re-calculated with updated fp16 gguf
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+ >* If using Kobold.cpp make sure you are on [v1.71.1](https://github.com/LostRuins/koboldcpp/releases/tag/v1.71.1) or later to take advantage of rope scaling
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  Quantized from Meta-Llama-3.1-8B-Claude fp16
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  * Weighted quantizations were creating using fp16 GGUF and groups_merged.txt in 88 chunks and n_ctx=512