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ibm-granite/granite-20b-code-base-8k - GGUF
This repo contains GGUF format model files for ibm-granite/granite-20b-code-base-8k.
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-20b-code-base-8k-Q2_K.gguf | Q2_K | 7.385 GB | smallest, significant quality loss - not recommended for most purposes |
granite-20b-code-base-8k-Q3_K_S.gguf | Q3_K_S | 8.321 GB | very small, high quality loss |
granite-20b-code-base-8k-Q3_K_M.gguf | Q3_K_M | 9.841 GB | very small, high quality loss |
granite-20b-code-base-8k-Q3_K_L.gguf | Q3_K_L | 10.930 GB | small, substantial quality loss |
granite-20b-code-base-8k-Q4_0.gguf | Q4_0 | 10.759 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
granite-20b-code-base-8k-Q4_K_S.gguf | Q4_K_S | 10.865 GB | small, greater quality loss |
granite-20b-code-base-8k-Q4_K_M.gguf | Q4_K_M | 11.940 GB | medium, balanced quality - recommended |
granite-20b-code-base-8k-Q5_0.gguf | Q5_0 | 13.054 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
granite-20b-code-base-8k-Q5_K_S.gguf | Q5_K_S | 13.054 GB | large, low quality loss - recommended |
granite-20b-code-base-8k-Q5_K_M.gguf | Q5_K_M | 13.792 GB | large, very low quality loss - recommended |
granite-20b-code-base-8k-Q6_K.gguf | Q6_K | 15.492 GB | very large, extremely low quality loss |
granite-20b-code-base-8k-Q8_0.gguf | Q8_0 | 20.006 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-20b-code-base-8k-GGUF --include "granite-20b-code-base-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-20b-code-base-8k-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
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Inference Providers
NEW
This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.
Model tree for tensorblock/granite-20b-code-base-8k-GGUF
Base model
ibm-granite/granite-20b-code-base-8kDatasets used to train tensorblock/granite-20b-code-base-8k-GGUF
Evaluation results
- pass@1 on MBPPself-reported43.800
- pass@1 on MBPP+self-reported51.600
- pass@1 on HumanEvalSynthesis(Python)self-reported48.200
- pass@1 on HumanEvalSynthesis(Python)self-reported50.000
- pass@1 on HumanEvalSynthesis(Python)self-reported59.100
- pass@1 on HumanEvalSynthesis(Python)self-reported32.300
- pass@1 on HumanEvalSynthesis(Python)self-reported40.900
- pass@1 on HumanEvalSynthesis(Python)self-reported35.400
- pass@1 on HumanEvalSynthesis(Python)self-reported17.100
- pass@1 on HumanEvalSynthesis(Python)self-reported18.300