README.md · tensorblock/mamba-130m-hf-GGUF at main

metadata

library_name: transformers
tags:
  - TensorBlock
  - GGUF
base_model: state-spaces/mamba-130m-hf

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state-spaces/mamba-130m-hf - GGUF

This repo contains GGUF format model files for state-spaces/mamba-130m-hf.

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
mamba-130m-hf-Q2_K.gguf	Q2_K	0.065 GB	smallest, significant quality loss - not recommended for most purposes
mamba-130m-hf-Q3_K_S.gguf	Q3_K_S	0.073 GB	very small, high quality loss
mamba-130m-hf-Q3_K_M.gguf	Q3_K_M	0.073 GB	very small, high quality loss
mamba-130m-hf-Q3_K_L.gguf	Q3_K_L	0.073 GB	small, substantial quality loss
mamba-130m-hf-Q4_0.gguf	Q4_0	0.081 GB	legacy; small, very high quality loss - prefer using Q3_K_M
mamba-130m-hf-Q4_K_S.gguf	Q4_K_S	0.084 GB	small, greater quality loss
mamba-130m-hf-Q4_K_M.gguf	Q4_K_M	0.084 GB	medium, balanced quality - recommended
mamba-130m-hf-Q5_0.gguf	Q5_0	0.092 GB	legacy; medium, balanced quality - prefer using Q4_K_M
mamba-130m-hf-Q5_K_S.gguf	Q5_K_S	0.094 GB	large, low quality loss - recommended
mamba-130m-hf-Q5_K_M.gguf	Q5_K_M	0.094 GB	large, very low quality loss - recommended
mamba-130m-hf-Q6_K.gguf	Q6_K	0.105 GB	very large, extremely low quality loss
mamba-130m-hf-Q8_0.gguf	Q8_0	0.132 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/mamba-130m-hf-GGUF --include "mamba-130m-hf-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/mamba-130m-hf-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'