tensorblock/QuartetAnemoi-70B-t0.0001-GGUF

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alchemonaut/QuartetAnemoi-70B-t0.0001 - GGUF

This repo contains GGUF format model files for alchemonaut/QuartetAnemoi-70B-t0.0001.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.

Filename	Quant type	File Size	Description
QuartetAnemoi-70B-t0.0001-Q2_K.gguf	Q2_K	25.462 GB	smallest, significant quality loss - not recommended for most purposes
QuartetAnemoi-70B-t0.0001-Q3_K_S.gguf	Q3_K_S	29.919 GB	very small, high quality loss
QuartetAnemoi-70B-t0.0001-Q3_K_M.gguf	Q3_K_M	33.275 GB	very small, high quality loss
QuartetAnemoi-70B-t0.0001-Q3_K_L.gguf	Q3_K_L	36.148 GB	small, substantial quality loss
QuartetAnemoi-70B-t0.0001-Q4_0.gguf	Q4_0	38.872 GB	legacy; small, very high quality loss - prefer using Q3_K_M
QuartetAnemoi-70B-t0.0001-Q4_K_S.gguf	Q4_K_S	39.250 GB	small, greater quality loss
QuartetAnemoi-70B-t0.0001-Q4_K_M.gguf	Q4_K_M	41.423 GB	medium, balanced quality - recommended
QuartetAnemoi-70B-t0.0001-Q5_0.gguf	Q5_0	47.461 GB	legacy; medium, balanced quality - prefer using Q4_K_M
QuartetAnemoi-70B-t0.0001-Q5_K_S.gguf	Q5_K_S	47.461 GB	large, low quality loss - recommended
QuartetAnemoi-70B-t0.0001-Q5_K_M.gguf	Q5_K_M	48.754 GB	large, very low quality loss - recommended
QuartetAnemoi-70B-t0.0001-Q8_0	Q6_K	73.292 GB	very large, extremely low quality loss
QuartetAnemoi-70B-t0.0001-Q6_K	Q8_0	56.587 GB	very large, extremely low quality loss - not recommended

Firstly, install Huggingface Client

pip install -U "huggingface_hub[cli]"

Then, downoad the individual model file the a local directory

huggingface-cli download tensorblock/QuartetAnemoi-70B-t0.0001-GGUF --include "QuartetAnemoi-70B-t0.0001-Q2_K.gguf" --local-dir MY_LOCAL_DIR

If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:

huggingface-cli download tensorblock/QuartetAnemoi-70B-t0.0001-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'