tensorblock/Mistral-Nemo-Base-2407-GGUF

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unsloth/Mistral-Nemo-Base-2407 - GGUF

This repo contains GGUF format model files for unsloth/Mistral-Nemo-Base-2407.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.

Filename	Quant type	File Size	Description
Mistral-Nemo-Base-2407-Q2_K.gguf	Q2_K	4.791 GB	smallest, significant quality loss - not recommended for most purposes
Mistral-Nemo-Base-2407-Q3_K_S.gguf	Q3_K_S	5.534 GB	very small, high quality loss
Mistral-Nemo-Base-2407-Q3_K_M.gguf	Q3_K_M	6.083 GB	very small, high quality loss
Mistral-Nemo-Base-2407-Q3_K_L.gguf	Q3_K_L	6.562 GB	small, substantial quality loss
Mistral-Nemo-Base-2407-Q4_0.gguf	Q4_0	7.072 GB	legacy; small, very high quality loss - prefer using Q3_K_M
Mistral-Nemo-Base-2407-Q4_K_S.gguf	Q4_K_S	7.120 GB	small, greater quality loss
Mistral-Nemo-Base-2407-Q4_K_M.gguf	Q4_K_M	7.477 GB	medium, balanced quality - recommended
Mistral-Nemo-Base-2407-Q5_0.gguf	Q5_0	8.519 GB	legacy; medium, balanced quality - prefer using Q4_K_M
Mistral-Nemo-Base-2407-Q5_K_S.gguf	Q5_K_S	8.519 GB	large, low quality loss - recommended
Mistral-Nemo-Base-2407-Q5_K_M.gguf	Q5_K_M	8.728 GB	large, very low quality loss - recommended
Mistral-Nemo-Base-2407-Q6_K.gguf	Q6_K	10.056 GB	very large, extremely low quality loss
Mistral-Nemo-Base-2407-Q8_0.gguf	Q8_0	13.022 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/Mistral-Nemo-Base-2407-GGUF --include "Mistral-Nemo-Base-2407-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/Mistral-Nemo-Base-2407-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'