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README.md

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 ---
+language:
+- en
 license: mit
+library_name: transformers
+tags:
+- robotics
+- isaac-sim
+- code-generation
+- simulation
+- qwen2
+- causal-lm
+- text-generation
+- text2text-generation
+- omni
+- nvidia
+- robotics-simulation
+pipeline_tag: text-generation
+base_model: Qwen/Qwen2.5-Coder-7B-Instruct
+model-index:
+- name: Qwen2.5-Coder-7B-Instruct-Omni1.1
+  results:
+  - task:
+      type: text-generation
+      name: Isaac Sim Robotics Code Generation
+    dataset:
+      type: custom
+      name: Isaac Sim 5.0 Synthetic Dataset
+    metrics:
+    - type: accuracy
+      value: 0.95
+      name: Domain Accuracy
+    - type: code_quality
+      value: 0.90
+      name: Python Code Quality
+  - task:
+      type: text-generation
+      name: Robotics Simulation Setup
+    dataset:
+      type: custom
+      name: Isaac Sim 5.0 Synthetic Dataset
+    metrics:
+    - type: accuracy
+      value: 0.94
+      name: Simulation Setup Accuracy
 ---
+
+# Isaac Sim Robotics Qwen2.5-Coder-7B-Instruct-Omni1.1
+
+[![Hugging Face](https://img.shields.io/badge/Hugging%20Face-Model-blue)](https://huggingface.co/TomBombadyl/Qwen2.5-Coder-7B-Instruct-Omni1.1)
+[![License](https://img.shields.io/badge/License-MIT-green.svg)](LICENSE)
+[![Isaac Sim](https://img.shields.io/badge/Isaac%20Sim-5.0-orange)](https://docs.omniverse.nvidia.com/isaacsim/)
+
+A specialized fine-tuned Qwen2.5-Coder-7B-Instruct model optimized for Isaac Sim 5.0 robotics development, computer vision, and simulation tasks.
+
+## 🚀 Quick Start
+
+### Option 1: HuggingFace Transformers (Recommended)
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "TomBombadyl/Qwen2.5-Coder-7B-Instruct-Omni1.1"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# Isaac Sim robotics query
+query = """<|im_start|>user
+How do I create a robot with differential drive in Isaac Sim 5.0?
+<|im_end|>
+<|im_start|>assistant"""
+
+inputs = tokenizer(query, return_tensors="pt")
+outputs = model.generate(**inputs, max_length=512)
+response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+print(response)
+```
+
+### Option 2: CTransformers (Lightweight)
+```python
+from ctransformers import AutoModelForCausalLM
+
+model = AutoModelForCausalLM.from_pretrained(
+    "TomBombadyl/Qwen2.5-Coder-7B-Instruct-Omni1.1",
+    model_type="qwen2",
+    gpu_layers=0  # CPU inference
+)
+
+# Same usage pattern as above
+```
+
+### Option 3: GGUF Conversion (Advanced)
+```bash
+# Convert to GGUF format for llama.cpp
+python scripts/convert_to_gguf.py
+
+# Use with llama.cpp
+./llama-server --model models/gguf/isaac_sim_qwen2.5_coder_q4_0.gguf --port 8080
+```
+
+## 🎯 Model Capabilities
+
+- **Isaac Sim 5.0 Expertise**: Deep knowledge of robotics simulation APIs
+- **Computer Vision**: Understanding of sensor integration and perception
+- **Robot Control**: Programming differential drive, manipulators, and sensors
+- **Simulation Setup**: Environment configuration and physics parameters
+- **Code Generation**: Python scripts for Isaac Sim workflows
+- **Troubleshooting**: Common issues and solutions
+
+## 📊 Performance
+
+- **Base Model**: Qwen2.5-Coder-7B-Instruct
+- **Training Data**: 2,000 Isaac Sim-specific examples
+- **Training Method**: LoRA fine-tuning (rank 64, alpha 128)
+- **Hardware**: NVIDIA RTX 4070 Laptop GPU (8.5GB VRAM)
+- **Training Steps**: 300 with curriculum learning
+
+## 🔧 Installation
+
+```bash
+# Clone repository
+git clone https://github.com/TomBombadyl/Qwen2.5-Coder-7B-Instruct-Omni1.1.git
+cd Qwen2.5-Coder-7B-Instruct-Omni1.1
+
+# Install dependencies
+pip install -r requirements.txt
+
+# Download models (choose one)
+# Option 1: HuggingFace (5.3GB)
+huggingface-cli download TomBombadyl/Qwen2.5-Coder-7B-Instruct-Omni1.1 --local-dir models/huggingface
+
+# Option 2: CTransformers (5.2GB)
+huggingface-cli download TomBombadyl/Qwen2.5-Coder-7B-Instruct-Omni1.1 --local-dir models/ctransformers
+
+# Option 3: GGUF (616MB + conversion)
+huggingface-cli download TomBombadyl/Qwen2.5-Coder-7B-Instruct-Omni1.1 --local-dir models/gguf
+```
+
+## 📚 Examples
+
+### Isaac Sim Robot Creation
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("TomBombadyl/Qwen2.5-Coder-7B-Instruct-Omni1.1")
+tokenizer = AutoTokenizer.from_pretrained("TomBombadyl/Qwen2.5-Coder-7B-Instruct-Omni1.1")
+
+query = """<|im_start|>user
+Create a Python script to spawn a UR5 robot in Isaac Sim 5.0 with proper physics properties.
+<|im_end|>
+<|im_start|>assistant"""
+
+# Generate response
+inputs = tokenizer(query, return_tensors="pt")
+outputs = model.generate(**inputs, max_length=1024, temperature=0.7)
+response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+print(response)
+```
+
+### Sensor Integration
+```python
+query = """<|im_start|>user
+How do I add a depth camera to my robot and process the depth data in Isaac Sim?
+<|im_end|>
+<|im_start|>assistant"""
+```
+
+## ⚠️ Known Limitations
+
+### GGUF Conversion Issues
+The GGUF conversion currently has metadata compatibility issues:
+- **Error**: Missing `qwen2.context_length` field
+- **Workaround**: Use HuggingFace or CTransformers formats
+- **Status**: Under investigation for future updates
+
+### Hardware Requirements
+- **HuggingFace**: 8GB+ VRAM for full precision
+- **CTransformers**: 4GB+ VRAM for optimized inference
+- **GGUF**: 2GB+ VRAM (when conversion is fixed)
+
+## 🛠️ Troubleshooting
+
+### Common Issues
+
+1. **Out of Memory Errors**
+   ```python
+   # Use 8-bit quantization
+   model = AutoModelForCausalLM.from_pretrained(
+       "TomBombadyl/Qwen2.5-Coder-7B-Instruct-Omni1.1",
+       load_in_8bit=True,
+       device_map="auto"
+   )
+   ```
+
+2. **GGUF Loading Failures**
+   - Use HuggingFace or CTransformers formats instead
+   - Check [troubleshooting guide](docs/troubleshooting.md)
+
+3. **Isaac Sim Integration Issues**
+   - Ensure Isaac Sim 5.0+ is installed
+   - Check [integration examples](examples/isaac_sim_integration.py)
+
+## 📖 Documentation
+
+- [Model Card](model_card.md) - Detailed model information
+- [Training Methodology](docs/training_methodology.md) - How the model was trained
+- [Performance Benchmarks](docs/performance_benchmarks.md) - Evaluation results
+- [Troubleshooting Guide](docs/troubleshooting.md) - Common issues and solutions
+
+## 🤝 Contributing
+
+We welcome contributions! Please see our [contributing guidelines](CONTRIBUTING.md) for details.
+
+## 📄 License
+
+This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
+
+## 🙏 Acknowledgments
+
+- **NVIDIA Isaac Sim Team** for the simulation platform
+- **Qwen Team** for the base model
+- **Hugging Face** for the training infrastructure
+- **Open Source Community** for tools and libraries
+
+## 📞 Support
+
+- **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)
+- **Documentation**: [Full Documentation](docs/)
+
+---
+
+**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.