File size: 2,202 Bytes
daaaf2a |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 |
---
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-4bit
The Model [mlx-community/granite-3b-code-instruct-4bit](https://huggingface.co/mlx-community/granite-3b-code-instruct-4bit) 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-4bit")
response = generate(model, tokenizer, prompt="hello", verbose=True)
```
|