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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.

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'
Downloads last month
65
GGUF
Model size
2.51B params
Architecture
gemma

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Inference API
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