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Original model: https://huggingface.co/brucethemoose/Yi-34B-200K-RPMerge
Steps:
- Convert to GGUF using llama.cpp (clone from source, install requirements, then run this)
python convert.py /mnt/d/LLM_Models/Yi-34B-200K-RPMerge/ --vocab-type hfft --outtype f32 --outfile Yi-34B-200K-RPMerge.gguf - Create imatrix (offload as much as you can to the GPU)
./imatrix -m /mnt/d/LLM_Models/Yi-34B-200K-RPMerge.gguf -f /mnt/d/LLM_Models/8k_random_data.txt -o /mnt/d/LLM_Models/Yi-34B-200K-RPMerge.imatrix.dat -ngl 20 - Quantize using imatrix
`./quantize --imatrix /mnt/d/LLM_Models/Yi-34B-200K-RPMerge.imatrix.dat /mnt/d/LLM_Models/Yi-34B-200K-RPMerge.gguf /mnt/d/LLM_Models/Yi-34B-200K-RPMerge.IQ2_XXS.gguf IQ2_XXS
I have also uploaded 8k_random_data.txt from this github discussion
And the importance matrix I made (Yi-34B-200K-RPMerge.imatrix.dat)
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