Text Generation
Transformers
Safetensors
MLX
gpt_bigcode
code
granite
conversational
Eval Results
Inference Endpoints
text-generation-inference
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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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+ base_model: ibm-granite/granite-34b-code-base
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+ datasets:
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+ - bigcode/commitpackft
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+ - TIGER-Lab/MathInstruct
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+ - meta-math/MetaMathQA
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+ - glaiveai/glaive-code-assistant-v3
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+ - glaive-function-calling-v2
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+ - bugdaryan/sql-create-context-instruction
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+ - garage-bAInd/Open-Platypus
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+ - nvidia/HelpSteer
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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-instruct
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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: 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: 62.2
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+ name: pass@1
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+ ---
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+
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+ # mlx-community/granite-34b-code-instruct-4bit
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+
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+ The Model [mlx-community/granite-34b-code-instruct-4bit](https://huggingface.co/mlx-community/granite-34b-code-instruct-4bit) was converted to MLX format from [ibm-granite/granite-34b-code-instruct](https://huggingface.co/ibm-granite/granite-34b-code-instruct) 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-instruct-4bit")
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+ response = generate(model, tokenizer, prompt="hello", verbose=True)
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+ ```
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