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ibm-granite/granite-8b-code-base-4k - GGUF
This repo contains GGUF format model files for ibm-granite/granite-8b-code-base-4k.
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 |
---|---|---|---|
granite-8b-code-base-4k-Q2_K.gguf | Q2_K | 2.852 GB | smallest, significant quality loss - not recommended for most purposes |
granite-8b-code-base-4k-Q3_K_S.gguf | Q3_K_S | 3.304 GB | very small, high quality loss |
granite-8b-code-base-4k-Q3_K_M.gguf | Q3_K_M | 3.674 GB | very small, high quality loss |
granite-8b-code-base-4k-Q3_K_L.gguf | Q3_K_L | 3.993 GB | small, substantial quality loss |
granite-8b-code-base-4k-Q4_0.gguf | Q4_0 | 4.276 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
granite-8b-code-base-4k-Q4_K_S.gguf | Q4_K_S | 4.305 GB | small, greater quality loss |
granite-8b-code-base-4k-Q4_K_M.gguf | Q4_K_M | 4.548 GB | medium, balanced quality - recommended |
granite-8b-code-base-4k-Q5_0.gguf | Q5_0 | 5.190 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
granite-8b-code-base-4k-Q5_K_S.gguf | Q5_K_S | 5.190 GB | large, low quality loss - recommended |
granite-8b-code-base-4k-Q5_K_M.gguf | Q5_K_M | 5.330 GB | large, very low quality loss - recommended |
granite-8b-code-base-4k-Q6_K.gguf | Q6_K | 6.161 GB | very large, extremely low quality loss |
granite-8b-code-base-4k-Q8_0.gguf | Q8_0 | 7.977 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-8b-code-base-4k-GGUF --include "granite-8b-code-base-4k-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-8b-code-base-4k-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
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Model tree for tensorblock/granite-8b-code-base-4k-GGUF
Base model
ibm-granite/granite-8b-code-base-4kDatasets used to train tensorblock/granite-8b-code-base-4k-GGUF
Evaluation results
- pass@1 on MBPPself-reported42.200
- pass@1 on MBPP+self-reported49.600
- pass@1 on HumanEvalSynthesis(Python)self-reported43.900
- pass@1 on HumanEvalSynthesis(Python)self-reported52.400
- pass@1 on HumanEvalSynthesis(Python)self-reported56.100
- pass@1 on HumanEvalSynthesis(Python)self-reported31.700
- pass@1 on HumanEvalSynthesis(Python)self-reported43.900
- pass@1 on HumanEvalSynthesis(Python)self-reported32.900
- pass@1 on HumanEvalSynthesis(Python)self-reported23.500
- pass@1 on HumanEvalSynthesis(Python)self-reported32.300