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---
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license: mit
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library_name: transformers
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tags:
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- nasa
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- space-science
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- research-assistant
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- phi3
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- rag
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- ollama
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language:
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- en
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pipeline_tag: text-generation
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---
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# NASA Research Assistant (Ollama Model)
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## Model Description
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This is a specialized language model trained on NASA research data, designed to assist with space science questions, research summarization, and technical explanations. The model is based on Phi-3 Mini 3.8B and has been optimized for scientific accuracy and detailed explanations.
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## Model Details
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- **Base Model**: Microsoft Phi-3 Mini 3.8B
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- **Training Data**: NASA research papers, mission reports, and scientific publications
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- **Model Size**: ~3.8B parameters
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- **License**: MIT
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- **Format**: GGUF (compatible with Ollama, llama.cpp)
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## Training Data Sources
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- NASA research papers from PubMed Central (3,938 documents processed)
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- NASA Taskbook project descriptions
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- NASA Open Science Data Repository
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- Space biology and microgravity research
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- Astronaut health and safety studies
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- Planetary science publications
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## Capabilities
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- **Question Answering**: Detailed responses about space science topics
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- **Research Summarization**: Condensing complex scientific papers
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- **Technical Explanations**: Breaking down aerospace concepts
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- **Mission Analysis**: Discussing NASA missions and findings
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- **Scientific Accuracy**: Trained on peer-reviewed research
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## Usage
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### With Ollama
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```bash
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# Pull the model
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ollama pull Ravurijeetendra12/ollama-nasa-model
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# Run the model
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ollama run Ravurijeetendra12/ollama-nasa-model
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```
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### Example Queries
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- "What are the main health risks for astronauts on long-duration missions?"
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- "Explain the effects of microgravity on plant growth"
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- "Summarize recent findings about space radiation exposure"
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- "How does the ISS maintain its orbit?"
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## Model Performance
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The model has been optimized for:
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- Scientific accuracy in space-related topics
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- Detailed explanations suitable for researchers and students
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- Proper citation of NASA research when applicable
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- Clear communication of complex concepts
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## Limitations
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- Knowledge cutoff based on training data (up to 2024)
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- Primarily focused on NASA and US space research
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- May not have complete coverage of very recent developments
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- Should not be used for mission-critical decisions without verification
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## Training Process
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1. **Data Collection**: Gathered NASA research papers and publications
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2. **Data Processing**: Cleaned and chunked scientific texts
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3. **RAG Integration**: Built retrieval-augmented generation system
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4. **Fine-tuning**: Applied LoRA fine-tuning on instruction pairs
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5. **Optimization**: Configured for scientific accuracy and detail
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## Technical Specifications
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- **Context Length**: 4096 tokens
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- **Temperature**: 0.7 (balanced creativity/accuracy)
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- **Top-p**: 0.9
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- **Quantization**: Q4_K_M (recommended for most use cases)
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## Citation
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If you use this model in your research, please cite:
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```bibtex
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@misc{nasa-ollama-model-2024,
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title={NASA Research Assistant: Specialized Language Model for Space Science},
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author={Ravurijeetendra12},
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year={2024},
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publisher={Hugging Face},
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url={https://huggingface.co/Ravurijeetendra12/ollama-nasa-model}
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}
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```
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## Contact
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For questions about this model or to report issues, please open an issue on the repository.
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## Acknowledgments
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- NASA for providing open access to research data
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- Microsoft for the Phi-3 base model
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- The open-source community for tools and libraries
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---
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*This model is designed for educational and research purposes. Always verify critical information with official NASA sources.*
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