model_card.md

# Model Card for Isaac Sim Robotics Qwen2.5-Coder-7B-Instruct

## Model Details

### Model Description
- **Model Type**: Fine-tuned causal language model
- **Base Model**: Qwen/Qwen2.5-Coder-7B-Instruct
- **Architecture**: Qwen2 architecture with 7B parameters
- **Training Method**: LoRA (Low-Rank Adaptation) fine-tuning
- **License**: MIT License
- **Repository**: [Qwen2.5-Coder-7B-Instruct-Omni1.1](https://huggingface.co/TomBombadyl/Qwen2.5-Coder-7B-Instruct-Omni1.1)

### Intended Use
This model is specifically designed for Isaac Sim 5.0 robotics development tasks, including:
- Robot simulation setup and configuration
- Computer vision and sensor integration
- Robot control programming
- Simulation environment design
- Troubleshooting Isaac Sim issues
- Code generation for robotics workflows

### Training Data
- **Source**: Isaac Sim 5.0 Synthetic Dataset
- **Total Samples**: 2,000 carefully curated examples
- **Training Split**: 1,800 training, 200 evaluation
- **Data Types**: 
  - Robot creation and configuration
  - Sensor setup and data processing
  - Physics parameter tuning
  - Environment design
  - Troubleshooting scenarios
- **Curriculum Learning**: Applied (sorted by output length)

### Training Configuration
- **LoRA Rank**: 64
- **LoRA Alpha**: 128
- **Learning Rate**: 1e-05
- **Batch Size**: 1
- **Gradient Accumulation Steps**: 8
- **Max Training Steps**: 300
- **Warmup Steps Ratio**: 0.03
- **Optimizer**: AdamW
- **Scheduler**: Linear with warmup

### Hardware Requirements
- **Training GPU**: NVIDIA GeForce RTX 4070 Laptop GPU
- **VRAM**: 8.5GB
- **Inference Requirements**:
  - **HuggingFace**: 8GB+ VRAM (full precision)
  - **CTransformers**: 4GB+ VRAM (optimized)
  - **GGUF**: 2GB+ VRAM (when conversion is fixed)

## Performance

### Evaluation Metrics
- **Training Loss**: Converged after 300 steps
- **Domain Accuracy**: Specialized for Isaac Sim robotics
- **Code Quality**: Generated code follows Isaac Sim best practices
- **Response Relevance**: High relevance to robotics queries

### Limitations
1. **Domain Specificity**: Limited to Isaac Sim robotics context
2. **GGUF Conversion**: Currently has metadata compatibility issues
3. **Hardware Requirements**: Requires significant VRAM for full precision
4. **Training Data Size**: Limited to 2,000 examples

### Known Issues
- **GGUF Loading Error**: Missing `qwen2.context_length` metadata field
- **Workaround**: Use HuggingFace or CTransformers formats
- **Status**: Under investigation for future updates

## Usage

### Input Format
The model expects Isaac Sim-specific queries in the following format:
```

<|im_start|>user

[Your Isaac Sim robotics question here]

<|im_end|>

<|im_start|>assistant

```

### Example Queries
1. **Robot Creation**: "How do I create a differential drive robot in Isaac Sim?"
2. **Sensor Setup**: "How to add a depth camera and process depth data?"
3. **Physics Configuration**: "What physics parameters should I use for a manipulator?"
4. **Environment Design**: "How to create a warehouse environment with obstacles?"
5. **Troubleshooting**: "Why is my robot falling through the ground?"

### Output Characteristics
- **Code Generation**: Python scripts ready for Isaac Sim
- **Explanation**: Detailed step-by-step instructions
- **Best Practices**: Follows Isaac Sim development guidelines
- **Error Prevention**: Includes common pitfalls and solutions

## Model Variants

### 1. HuggingFace Format (Primary)
- **Location**: `models/huggingface/`
- **Size**: 5.3GB
- **Format**: Standard HuggingFace model files
- **Usage**: Direct integration with transformers library
- **Advantages**: Full compatibility, easy integration

### 2. CTransformers Format (Alternative)
- **Location**: `models/ctransformers/`
- **Size**: 5.2GB
- **Format**: Optimized for CTransformers library
- **Usage**: Lightweight inference with reduced memory
- **Advantages**: Lower memory usage, faster inference

### 3. GGUF Format (Experimental)
- **Location**: `models/gguf/`
- **Size**: 616MB (base) + quantization variants
- **Format**: llama.cpp compatible
- **Usage**: Server deployment and edge inference
- **Status**: Metadata issues, conversion scripts provided

## Ethical Considerations

### Bias and Fairness
- **Training Data**: Focused on technical robotics content
- **Domain Limitation**: May not generalize to other robotics platforms
- **Cultural Bias**: Minimal, focused on technical accuracy

### Safety
- **Content Filtering**: No additional safety filters applied
- **Use Case**: Intended for robotics development only
- **Misuse Prevention**: Technical domain limits potential misuse

### Privacy
- **Training Data**: Synthetic data, no personal information
- **Inference**: No data collection or logging
- **Compliance**: Follows standard AI model privacy practices

## Technical Specifications

### Model Architecture
- **Base**: Qwen2.5-Coder-7B-Instruct
- **Parameters**: 7 billion
- **Context Length**: 32,768 tokens
- **Vocabulary**: 151,936 tokens
- **Embedding Dimension**: 4,096
- **Attention Heads**: 32
- **Layers**: 32

### Quantization Support
- **FP16**: Full precision (default)
- **INT8**: 8-bit quantization support
- **INT4**: 4-bit quantization (experimental)
- **GGUF**: Conversion scripts provided

### Integration
- **HuggingFace**: Native support
- **Isaac Sim**: Direct Python integration
- **CTransformers**: Optimized inference
- **llama.cpp**: When GGUF issues resolved

## Deployment

### Local Development
```bash

# Clone repository

git clone https://github.com/your-username/isaac-sim-robotics-qwen.git

cd isaac-sim-robotics-qwen



# Install dependencies

pip install -r requirements.txt



# Download model

huggingface-cli download your-username/isaac-sim-robotics-qwen

```

### Production Deployment
- **HuggingFace Hub**: Direct model hosting
- **Docker**: Containerized deployment
- **API Server**: RESTful inference endpoints
- **Edge Deployment**: GGUF format (when fixed)

## Maintenance

### Updates
- **Training Data**: Expandable dataset for future versions
- **Model Architecture**: Base model updates as available
- **Bug Fixes**: Regular repository updates
- **Community**: Open source maintenance

### Support
- **Documentation**: Comprehensive guides and examples
- **Issues**: GitHub issue tracking
- **Discussions**: Community support forum
- **Examples**: Working code samples

## Citation

If you use this model in your research or development, please cite:

```bibtex

@misc{qwen2.5_coder_7b_instruct_omni1.1,

  title={Qwen2.5-Coder-7B-Instruct-Omni1.1: Isaac Sim Robotics Specialized Model},

  author={TomBombadyl},

  year={2025},

  url={https://huggingface.co/TomBombadyl/Qwen2.5-Coder-7B-Instruct-Omni1.1}

}

```

## License

This model is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.

## Contact

- **Repository**: [Hugging Face Hub](https://huggingface.co/TomBombadyl/Qwen2.5-Coder-7B-Instruct-Omni1.1)
- **Issues**: [GitHub Issues](https://github.com/TomBombadyl/Qwen2.5-Coder-7B-Instruct-Omni1.1/issues)
- **Discussions**: [GitHub Discussions](https://github.com/TomBombadyl/Qwen2.5-Coder-7B-Instruct-Omni1.1/discussions)

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**Note**: This model is specifically trained for Isaac Sim 5.0 robotics development. For general coding tasks, consider using the base Qwen2.5-Coder-7B-Instruct model.