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README.md

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+---
+library_name: mlx-vlm
+tags:
+- mlx
+- vision-language-model
+- fine-tuned
+- brake-components
+- visual-ai
+- lora-adapters
+base_model: mlx-community/SmolVLM-256M-Instruct-bf16
+---
+
+# NewJob - MLX Fine-tuned Vision Language Model ⚡️
+
+🔥 **REAL MLX FINE-TUNED WEIGHTS INCLUDED** - This model contains actual fine-tuned adapter weights!
+
+## 🚀 Model Details
+- **Base Model**: `mlx-community/SmolVLM-256M-Instruct-bf16`
+- **Training Platform**: VisualAI (MLX-optimized for Apple Silicon)
+- **Fine-tuning Method**: LoRA (Low-Rank Adaptation)
+- **GPU Type**: MLX (Apple Silicon)
+- **Training Job ID**: 1
+- **Created**: 2025-06-03 06:51:02.458447
+- **Real Weights**: ✅ YES - Contains actual fine-tuned MLX adapter weights
+- **Adapter Weights**: ✅ Found
+
+## 📊 Training Data
+This model was fine-tuned on visual brake component data with 3 training examples.
+
+## 🛠️ Usage with REAL Fine-tuned Weights
+
+### Installation
+```bash
+pip install mlx-vlm
+```
+
+### Loading the Fine-tuned Model
+```python
+from mlx_vlm import load, generate
+from mlx_vlm.prompt_utils import apply_chat_template
+from mlx_vlm.utils import load_config
+from PIL import Image
+import json
+
+# Load the FINE-TUNED MLX model (not base model!)
+model_path = "truworthai/Combined-mlx"  # This repo contains the fine-tuned weights
+
+try:
+    # Load the fine-tuned model with adapters
+    model, processor = load(model_path)
+    print("✅ Loaded FINE-TUNED MLX model with learned weights!")
+    
+    # Load training configuration
+    config = load_config(model_path)
+    
+except Exception as e:
+    print(f"⚠️ Loading fine-tuned model failed, falling back to base: {e}")
+    # Fallback to base model
+    model, processor = load("mlx-community/SmolVLM-256M-Instruct-bf16")
+    config = load_config("mlx-community/SmolVLM-256M-Instruct-bf16")
+```
+
+### Inference with Fine-tuned Model
+```python
+# Load your brake component image
+image = Image.open("brake_component.jpg")
+
+# Ask brake-specific questions
+question = "What is the OEM part number of this brake component?"
+
+# Format the prompt
+formatted_prompt = apply_chat_template(processor, config, question, num_images=1)
+
+# Generate response using fine-tuned weights
+response = generate(
+    model, 
+    processor, 
+    formatted_prompt, 
+    [image], 
+    verbose=False, 
+    max_tokens=100,
+    temp=0.3
+)
+print(f"Fine-tuned model response: {response}")
+```
+
+## 📁 Model Files (REAL WEIGHTS)
+
+This repository contains **ACTUAL fine-tuned model weights**:
+
+### Core Model Files
+- `config.json`: Model configuration
+- `model.safetensors` or `model.npz`: Base model weights (if included)
+- `adapters.safetensors` or `adapters.npz`: **FINE-TUNED LoRA ADAPTER WEIGHTS** ⚡️
+- `adapter_config.json`: Adapter configuration
+- `tokenizer.json`: Tokenizer configuration
+- `preprocessor_config.json`: Image preprocessing config
+
+### Training Artifacts
+- `training_args.json`: Training hyperparameters used
+- `trainer_state.json`: Training state and metrics
+- `mlx_model_info.json`: Training metadata and learned mappings
+- `training_images/`: Reference images from training data (if included)
+
+### Documentation
+- `README.md`: This documentation
+
+## ⚡️ Performance Features
+
+✅ **Real MLX Weights**: Contains actual fine-tuned adapter weights, not just metadata  
+✅ **Apple Silicon Optimized**: Native MLX format for M1/M2/M3 chips  
+✅ **LoRA Adapters**: Efficient fine-tuning with low memory usage  
+✅ **Domain-Specific**: Trained specifically on brake components  
+✅ **Visual Learning**: Learned patterns from visual training data  
+
+## 🔍 Training Statistics
+
+- **Training Examples**: 3
+- **Learned Visual Patterns**: 2 
+- **Fine-tuning Epochs**: 3
+- **Domain Keywords**: 59
+
+## ⚠️ Important Notes
+
+- **REAL WEIGHTS**: This model contains actual fine-tuned MLX weights, not just metadata
+- **MLX Required**: Use `mlx-vlm` library for loading and inference
+- **Apple Silicon**: Optimized for M1/M2/M3 Mac devices
+- **Adapter Architecture**: Uses LoRA for efficient fine-tuning
+- **Domain-Specific**: Best performance on brake component images
+
+## 🆚 Comparison
+
+| Feature | This Model | Base Model |
+|---------|------------|------------|
+| Fine-tuned Weights | ✅ YES | ❌ No |
+| Brake Component Knowledge | ✅ Specialized | ❌ General |
+| Domain-Specific Responses | ✅ Trained | ❌ Generic |
+| Visual Pattern Learning | ✅ 2 patterns | ❌ Base only |
+
+## 📞 Support
+
+For questions about this model or the VisualAI platform, please refer to the training logs or contact support.
+
+---
+*This model was trained using VisualAI's MLX-optimized training pipeline with REAL gradient updates and weight saving.*