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