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  <b>Special request.</b> Quantized from fp32 with love. If you can't fit IQ quants in your VRAM, try using the K quants in this repo instead.
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- * Weighted quantizations created using this [process](https://huggingface.co/jukofyork/WizardLM-2-8x22B-imatrix)
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  * Calculated in 88 chunks with n_ctx=512 using groups_merged.txt
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  For a brief rundown of iMatrix quant performance please see this [PR](https://github.com/ggerganov/llama.cpp/pull/5747)
 
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  <b>Special request.</b> Quantized from fp32 with love. If you can't fit IQ quants in your VRAM, try using the K quants in this repo instead.
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+ * The [.imatrix](https://huggingface.co/InferenceIllusionist/Llama-3-70B-Instruct-Storywriter-iMat-GGUF/resolve/main/Llama-3-70B-Instruct-Storywriter.imatrix?download=true) file in this repo was created using this [process](https://huggingface.co/jukofyork/WizardLM-2-8x22B-imatrix)
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  * Calculated in 88 chunks with n_ctx=512 using groups_merged.txt
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  For a brief rundown of iMatrix quant performance please see this [PR](https://github.com/ggerganov/llama.cpp/pull/5747)