Update README.md

README.md

@@ -3,4 +3,38 @@ base_model:
 - mistralai/Mistral-7B-v0.1
 ---
 
-4 bit quantized version by MLX
+# Mistral-7B-v0.1-4bit-mlx
+
+A 4-bit LoRA‑fine‑tuned Mistral-7B model in Apple MLX format, created via the MLX Examples LoRA tutorial.
+
+---
+
+## 🚀 Overview
+
+This model was created by following the MLX LoRA tutorial:
+
+- **LoRA fine‑tuning** applied on Mistral‑7B using low‑rank adapters  
+- **Model fusion** performed with `convert.py` to combine base weights and LoRA adapters  
+- **Quantized to 4-bit** for memory efficiency on Apple Silicon devices  
+- Packaged in MLX format, ready for downstream use via `mlx-lm`
+
+The pipeline is fully automated based on `mlx-examples/lora/convert.py`, with no manual weight editing.
+
+---
+
+## 📦 Model Packaging
+
+| File                | Description                                  |
+|---------------------|----------------------------------------------|
+| `weights.npz`       | Fused weights: base + LoRA adapters         |
+| `config.json`       | Model configuration & quantization metadata |
+| `tokenizer.model`   | SentencePiece tokenizer for Mistral-7B     |
+
+---
+
+## 💡 Usage
+
+### Inference with `mlx-lm`
+
+```bash
+pip install mlx-lm