tensorblock/Mistral-Ita-7b-GGUF

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DeepMount00/Mistral-Ita-7b - GGUF

This repo contains GGUF format model files for DeepMount00/Mistral-Ita-7b.

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

Prompt template

Model file specification

Filename	Quant type	File Size	Description
Mistral-Ita-7b-Q2_K.gguf	Q2_K	2.532 GB	smallest, significant quality loss - not recommended for most purposes
Mistral-Ita-7b-Q3_K_S.gguf	Q3_K_S	2.947 GB	very small, high quality loss
Mistral-Ita-7b-Q3_K_M.gguf	Q3_K_M	3.277 GB	very small, high quality loss
Mistral-Ita-7b-Q3_K_L.gguf	Q3_K_L	3.560 GB	small, substantial quality loss
Mistral-Ita-7b-Q4_0.gguf	Q4_0	3.827 GB	legacy; small, very high quality loss - prefer using Q3_K_M
Mistral-Ita-7b-Q4_K_S.gguf	Q4_K_S	3.856 GB	small, greater quality loss
Mistral-Ita-7b-Q4_K_M.gguf	Q4_K_M	4.068 GB	medium, balanced quality - recommended
Mistral-Ita-7b-Q5_0.gguf	Q5_0	4.654 GB	legacy; medium, balanced quality - prefer using Q4_K_M
Mistral-Ita-7b-Q5_K_S.gguf	Q5_K_S	4.654 GB	large, low quality loss - recommended
Mistral-Ita-7b-Q5_K_M.gguf	Q5_K_M	4.779 GB	large, very low quality loss - recommended
Mistral-Ita-7b-Q6_K.gguf	Q6_K	5.534 GB	very large, extremely low quality loss
Mistral-Ita-7b-Q8_0.gguf	Q8_0	7.167 GB	very large, extremely low quality loss - not recommended

Downloading instruction

Command line

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-Ita-7b-GGUF --include "Mistral-Ita-7b-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-Ita-7b-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'