mlx-community/granite-20b-code-base-4bit
The Model mlx-community/granite-20b-code-base-4bit was converted to MLX format from ibm-granite/granite-20b-code-base using mlx-lm version 0.13.0.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/granite-20b-code-base-4bit")
response = generate(model, tokenizer, prompt="hello", verbose=True)
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Datasets used to train mlx-community/granite-20b-code-base-4bit
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