tensorblock/FusionNet_linear-GGUF

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

TomGrc/FusionNet_linear - GGUF

This repo contains GGUF format model files for TomGrc/FusionNet_linear.

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

### System:
{system_prompt}

### User:
{prompt}

### Assistant:

Filename	Quant type	File Size	Description
FusionNet_linear-Q2_K.gguf	Q2_K	4.003 GB	smallest, significant quality loss - not recommended for most purposes
FusionNet_linear-Q3_K_S.gguf	Q3_K_S	4.665 GB	very small, high quality loss
FusionNet_linear-Q3_K_M.gguf	Q3_K_M	5.196 GB	very small, high quality loss
FusionNet_linear-Q3_K_L.gguf	Q3_K_L	5.651 GB	small, substantial quality loss
FusionNet_linear-Q4_0.gguf	Q4_0	6.072 GB	legacy; small, very high quality loss - prefer using Q3_K_M
FusionNet_linear-Q4_K_S.gguf	Q4_K_S	6.119 GB	small, greater quality loss
FusionNet_linear-Q4_K_M.gguf	Q4_K_M	6.462 GB	medium, balanced quality - recommended
FusionNet_linear-Q5_0.gguf	Q5_0	7.397 GB	legacy; medium, balanced quality - prefer using Q4_K_M
FusionNet_linear-Q5_K_S.gguf	Q5_K_S	7.397 GB	large, low quality loss - recommended
FusionNet_linear-Q5_K_M.gguf	Q5_K_M	7.598 GB	large, very low quality loss - recommended
FusionNet_linear-Q6_K.gguf	Q6_K	8.805 GB	very large, extremely low quality loss
FusionNet_linear-Q8_0.gguf	Q8_0	11.404 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/FusionNet_linear-GGUF --include "FusionNet_linear-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/FusionNet_linear-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'