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meta-llama/CodeLlama-34b-hf - GGUF

This repo contains GGUF format model files for meta-llama/CodeLlama-34b-hf.

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
CodeLlama-34b-hf-Q2_K.gguf Q2_K 12.506 GB smallest, significant quality loss - not recommended for most purposes
CodeLlama-34b-hf-Q3_K_S.gguf Q3_K_S 14.605 GB very small, high quality loss
CodeLlama-34b-hf-Q3_K_M.gguf Q3_K_M 16.306 GB very small, high quality loss
CodeLlama-34b-hf-Q3_K_L.gguf Q3_K_L 17.772 GB small, substantial quality loss
CodeLlama-34b-hf-Q4_0.gguf Q4_0 19.052 GB legacy; small, very high quality loss - prefer using Q3_K_M
CodeLlama-34b-hf-Q4_K_S.gguf Q4_K_S 19.192 GB small, greater quality loss
CodeLlama-34b-hf-Q4_K_M.gguf Q4_K_M 20.220 GB medium, balanced quality - recommended
CodeLlama-34b-hf-Q5_0.gguf Q5_0 23.237 GB legacy; medium, balanced quality - prefer using Q4_K_M
CodeLlama-34b-hf-Q5_K_S.gguf Q5_K_S 23.237 GB large, low quality loss - recommended
CodeLlama-34b-hf-Q5_K_M.gguf Q5_K_M 23.839 GB large, very low quality loss - recommended
CodeLlama-34b-hf-Q6_K.gguf Q6_K 27.684 GB very large, extremely low quality loss
CodeLlama-34b-hf-Q8_0.gguf Q8_0 35.856 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/CodeLlama-34b-hf-GGUF --include "CodeLlama-34b-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/CodeLlama-34b-hf-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
339
GGUF
Model size
33.7B params
Architecture
llama

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Inference Examples
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