codegemma-2b-GGUF / README.md
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metadata
library_name: transformers
license: gemma
license_link: https://ai.google.dev/gemma/terms
extra_gated_heading: Access CodeGemma on Hugging Face
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  To access CodeGemma on Hugging Face, you’re required to review and agree to
  Google’s usage license. To do this, please ensure you’re logged-in to Hugging
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base_model: google/codegemma-2b
tags:
  - TensorBlock
  - GGUF
TensorBlock

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google/codegemma-2b - GGUF

This repo contains GGUF format model files for google/codegemma-2b.

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

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## Prompt template

Model file specification

Filename Quant type File Size Description
codegemma-2b-Q2_K.gguf Q2_K 1.158 GB smallest, significant quality loss - not recommended for most purposes
codegemma-2b-Q3_K_S.gguf Q3_K_S 1.288 GB very small, high quality loss
codegemma-2b-Q3_K_M.gguf Q3_K_M 1.384 GB very small, high quality loss
codegemma-2b-Q3_K_L.gguf Q3_K_L 1.466 GB small, substantial quality loss
codegemma-2b-Q4_0.gguf Q4_0 1.551 GB legacy; small, very high quality loss - prefer using Q3_K_M
codegemma-2b-Q4_K_S.gguf Q4_K_S 1.560 GB small, greater quality loss
codegemma-2b-Q4_K_M.gguf Q4_K_M 1.630 GB medium, balanced quality - recommended
codegemma-2b-Q5_0.gguf Q5_0 1.799 GB legacy; medium, balanced quality - prefer using Q4_K_M
codegemma-2b-Q5_K_S.gguf Q5_K_S 1.799 GB large, low quality loss - recommended
codegemma-2b-Q5_K_M.gguf Q5_K_M 1.840 GB large, very low quality loss - recommended
codegemma-2b-Q6_K.gguf Q6_K 2.062 GB very large, extremely low quality loss
codegemma-2b-Q8_0.gguf Q8_0 2.669 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/codegemma-2b-GGUF --include "codegemma-2b-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/codegemma-2b-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'