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tensorblock/codegemma-7b-it-GGUF

🤗 Hugging Face sourceapache-2.07B activated132 GBGGUF✓ 2 checksumsupdated today
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curl -fsSL https://pirateface.co/package.sh | bash -s -- --repo tensorblock/codegemma-7b-it-GGUF ./model-folder
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unsloth/codegemma-7b-it - GGUF

This repo contains GGUF format model files for unsloth/codegemma-7b-it.

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
<bos><start_of_turn>user
{prompt}<end_of_turn>
<start_of_turn>model

Model file specification

Filename Quant type File Size Description
codegemma-7b-it-Q2_K.gguf Q2_K 3.481 GB smallest, significant quality loss - not recommended for most purposes
codegemma-7b-it-Q3_K_S.gguf Q3_K_S 3.982 GB very small, high quality loss
codegemma-7b-it-Q3_K_M.gguf Q3_K_M 4.369 GB very small, high quality loss
codegemma-7b-it-Q3_K_L.gguf Q3_K_L 4.709 GB small, substantial quality loss
codegemma-7b-it-Q4_0.gguf Q4_0 5.012 GB legacy; small, very high quality loss - prefer using Q3_K_M
codegemma-7b-it-Q4_K_S.gguf Q4_K_S 5.046 GB small, greater quality loss
codegemma-7b-it-Q4_K_M.gguf Q4_K_M 5.330 GB medium, balanced quality - recommended
codegemma-7b-it-Q5_0.gguf Q5_0 5.981 GB legacy; medium, balanced quality - prefer using Q4_K_M
codegemma-7b-it-Q5_K_S.gguf Q5_K_S 5.981 GB large, low quality loss - recommended
codegemma-7b-it-Q5_K_M.gguf Q5_K_M 6.145 GB large, very low quality loss - recommended
codegemma-7b-it-Q6_K.gguf Q6_K 7.010 GB very large, extremely low quality loss
codegemma-7b-it-Q8_0.gguf Q8_0 9.078 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-7b-it-GGUF --include "codegemma-7b-it-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-7b-it-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'