tensorblock/granite-34b-code-instruct-8k-GGUF

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ibm-granite/granite-34b-code-instruct-8k - GGUF

This repo contains GGUF format model files for ibm-granite/granite-34b-code-instruct-8k.

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

Run them on the TensorBlock client using your local machine ↗

Prompt template

System:
{system_prompt}

Question:
{prompt}

Answer:

Model file specification

Filename	Quant type	File Size	Description
granite-34b-code-instruct-8k-Q2_K.gguf	Q2_K	12.207 GB	smallest, significant quality loss - not recommended for most purposes
granite-34b-code-instruct-8k-Q3_K_S.gguf	Q3_K_S	13.791 GB	very small, high quality loss
granite-34b-code-instruct-8k-Q3_K_M.gguf	Q3_K_M	16.361 GB	very small, high quality loss
granite-34b-code-instruct-8k-Q3_K_L.gguf	Q3_K_L	18.207 GB	small, substantial quality loss
granite-34b-code-instruct-8k-Q4_0.gguf	Q4_0	17.917 GB	legacy; small, very high quality loss - prefer using Q3_K_M
granite-34b-code-instruct-8k-Q4_K_S.gguf	Q4_K_S	18.110 GB	small, greater quality loss
granite-34b-code-instruct-8k-Q4_K_M.gguf	Q4_K_M	19.915 GB	medium, balanced quality - recommended
granite-34b-code-instruct-8k-Q5_0.gguf	Q5_0	21.800 GB	legacy; medium, balanced quality - prefer using Q4_K_M
granite-34b-code-instruct-8k-Q5_K_S.gguf	Q5_K_S	21.800 GB	large, low quality loss - recommended
granite-34b-code-instruct-8k-Q5_K_M.gguf	Q5_K_M	23.050 GB	large, very low quality loss - recommended
granite-34b-code-instruct-8k-Q6_K.gguf	Q6_K	25.926 GB	very large, extremely low quality loss
granite-34b-code-instruct-8k-Q8_0.gguf	Q8_0	33.518 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/granite-34b-code-instruct-8k-GGUF --include "granite-34b-code-instruct-8k-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/granite-34b-code-instruct-8k-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'