metadata
base_model:
- mistralai/Mistral-7B-v0.1
tags:
- mlx
Mistral7B-v0.1-4bit-mlx-LoRA-WikiSQL
A 4-bit LoRA-fine-tuned Mistral-7B model for WikiSQL tasks, via Appleβs MLX framework and the lora.py.
This model was converted to MLX format from Hinova/mistral-7B-v0.1-4bit-mlx.
Refer to the original model card for more details on the model.
π Overview
This model was trained using the MLX Examples LoRA tutorial:
- Fine-tuning based on
lora.py(ml-explore/mlx-examples/lora) - Adapted Mistral-7B on the WikiSQL dataset
- Applied low-rank ΞW adapters with LoRA, freezing base weights
- Quantized to 4-bit for Apple Silicon efficiency
- Packaged in MLX format for seamless inference via
mlx-lm
π¦ Model Files
| File | Description |
|---|---|
weights.npz |
Fused weights: base + LoRA adapters |
config.json |
Model config with quantization metadata |
tokenizer.model |
SentencePiece tokenizer for Mistral-7B |
π‘ How to Use
Install
pip install mlx-lm
## Use with mlx
```bash
pip install mlx
git clone https://github.com/ml-explore/mlx-examples.git
cd mlx-examples/llms/hf_llm
python generate.py --model Hinova/mistral7b-v0.1-4bit-mlx-lora-wikisql --prompt "My name is"