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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ library_name: transformers
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+ tags:
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+ - code
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+ - granite
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+ - mlx
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+ datasets:
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+ - codeparrot/github-code-clean
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+ - bigcode/starcoderdata
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+ - open-web-math/open-web-math
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+ - math-ai/StackMathQA
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+ metrics:
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+ - code_eval
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+ pipeline_tag: text-generation
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+ inference: true
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+ model-index:
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+ - name: granite-34b-code-base
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+ results:
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+ - task:
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+ type: text-generation
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+ dataset:
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+ name: MBPP
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+ type: mbpp
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+ metrics:
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+ - type: pass@1
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+ value: 47.2
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+ name: pass@1
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+ - task:
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+ type: text-generation
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+ dataset:
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+ name: MBPP+
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+ type: evalplus/mbppplus
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+ metrics:
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+ - type: pass@1
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+ value: 53.1
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+ name: pass@1
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+ - task:
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+ type: text-generation
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+ dataset:
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+ name: HumanEvalSynthesis(Python)
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+ type: bigcode/humanevalpack
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+ metrics:
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+ - type: pass@1
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+ value: 48.2
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+ name: pass@1
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+ - type: pass@1
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+ value: 54.9
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+ name: pass@1
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+ - type: pass@1
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+ value: 61.6
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+ name: pass@1
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+ - type: pass@1
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+ value: 40.2
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+ name: pass@1
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+ name: pass@1
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+ - type: pass@1
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+ value: 12.2
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+ name: pass@1
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+ ---
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+
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+ # mlx-community/granite-34b-code-base-8bit
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+
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+ The Model [mlx-community/granite-34b-code-base-8bit](https://huggingface.co/mlx-community/granite-34b-code-base-8bit) was converted to MLX format from [ibm-granite/granite-34b-code-base](https://huggingface.co/ibm-granite/granite-34b-code-base) using mlx-lm version **0.13.0**.
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+
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+ ## Use with mlx
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+
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+ ```bash
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+ pip install mlx-lm
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+ ```
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+
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+ ```python
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+ from mlx_lm import load, generate
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+
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+ model, tokenizer = load("mlx-community/granite-34b-code-base-8bit")
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+ response = generate(model, tokenizer, prompt="hello", verbose=True)
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+ ```
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