---
license: apache-2.0
library_name: transformers
tags:
- code
- mlx
base_model: ibm-granite/granite-3b-code-base
datasets:
- bigcode/commitpackft
- TIGER-Lab/MathInstruct
- meta-math/MetaMathQA
- glaiveai/glaive-code-assistant-v3
- glaive-function-calling-v2
- bugdaryan/sql-create-context-instruction
- garage-bAInd/Open-Platypus
- nvidia/HelpSteer
metrics:
- code_eval
pipeline_tag: text-generation
inference: false
model-index:
- name: granite-3b-code-instruct
  results:
  - task:
      type: text-generation
    dataset:
      name: HumanEvalSynthesis(Python)
      type: bigcode/humanevalpack
    metrics:
    - type: pass@1
      value: 51.2
      name: pass@1
    - type: pass@1
      value: 43.9
      name: pass@1
    - type: pass@1
      value: 41.5
      name: pass@1
    - type: pass@1
      value: 31.7
      name: pass@1
    - type: pass@1
      value: 40.2
      name: pass@1
    - type: pass@1
      value: 29.3
      name: pass@1
    - type: pass@1
      value: 39.6
      name: pass@1
    - type: pass@1
      value: 26.8
      name: pass@1
    - type: pass@1
      value: 39.0
      name: pass@1
    - type: pass@1
      value: 14.0
      name: pass@1
    - type: pass@1
      value: 23.8
      name: pass@1
    - type: pass@1
      value: 12.8
      name: pass@1
    - type: pass@1
      value: 26.8
      name: pass@1
    - type: pass@1
      value: 28.0
      name: pass@1
    - type: pass@1
      value: 33.5
      name: pass@1
    - type: pass@1
      value: 27.4
      name: pass@1
    - type: pass@1
      value: 31.7
      name: pass@1
    - type: pass@1
      value: 16.5
      name: pass@1
---

# mlx-community/granite-3b-code-instruct-8bit

The Model [mlx-community/granite-3b-code-instruct-8bit](https://huggingface.co/mlx-community/granite-3b-code-instruct-8bit) was converted to MLX format from [ibm-granite/granite-3b-code-instruct](https://huggingface.co/ibm-granite/granite-3b-code-instruct) using mlx-lm version **0.12.0**.

## Use with mlx

```bash
pip install mlx-lm
```

```python
from mlx_lm import load, generate

model, tokenizer = load("mlx-community/granite-3b-code-instruct-8bit")
response = generate(model, tokenizer, prompt="hello", verbose=True)
```