tensorblock/CroissantLLMChat-v0.1-GGUF

Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server

croissantllm/CroissantLLMChat-v0.1 - GGUF

This repo contains GGUF format model files for croissantllm/CroissantLLMChat-v0.1.

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

Prompt template

<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant

Model file specification

Filename	Quant type	File Size	Description
CroissantLLMChat-v0.1-Q2_K.gguf	Q2_K	0.520 GB	smallest, significant quality loss - not recommended for most purposes
CroissantLLMChat-v0.1-Q3_K_S.gguf	Q3_K_S	0.597 GB	very small, high quality loss
CroissantLLMChat-v0.1-Q3_K_M.gguf	Q3_K_M	0.655 GB	very small, high quality loss
CroissantLLMChat-v0.1-Q3_K_L.gguf	Q3_K_L	0.692 GB	small, substantial quality loss
CroissantLLMChat-v0.1-Q4_0.gguf	Q4_0	0.722 GB	legacy; small, very high quality loss - prefer using Q3_K_M
CroissantLLMChat-v0.1-Q4_K_S.gguf	Q4_K_S	0.757 GB	small, greater quality loss
CroissantLLMChat-v0.1-Q4_K_M.gguf	Q4_K_M	0.812 GB	medium, balanced quality - recommended
CroissantLLMChat-v0.1-Q5_0.gguf	Q5_0	0.871 GB	legacy; medium, balanced quality - prefer using Q4_K_M
CroissantLLMChat-v0.1-Q5_K_S.gguf	Q5_K_S	0.886 GB	large, low quality loss - recommended
CroissantLLMChat-v0.1-Q5_K_M.gguf	Q5_K_M	0.932 GB	large, very low quality loss - recommended
CroissantLLMChat-v0.1-Q6_K.gguf	Q6_K	1.090 GB	very large, extremely low quality loss
CroissantLLMChat-v0.1-Q8_0.gguf	Q8_0	1.332 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/CroissantLLMChat-v0.1-GGUF --include "CroissantLLMChat-v0.1-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/CroissantLLMChat-v0.1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'