Instructions to use MarshallDoyle/NASA-Systems-Engineering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MarshallDoyle/NASA-Systems-Engineering with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MarshallDoyle/NASA-Systems-Engineering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use MarshallDoyle/NASA-Systems-Engineering with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf MarshallDoyle/NASA-Systems-Engineering:Q4_K_M # Run inference directly in the terminal: llama cli -hf MarshallDoyle/NASA-Systems-Engineering:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf MarshallDoyle/NASA-Systems-Engineering:Q4_K_M # Run inference directly in the terminal: llama cli -hf MarshallDoyle/NASA-Systems-Engineering:Q4_K_M
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf MarshallDoyle/NASA-Systems-Engineering:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf MarshallDoyle/NASA-Systems-Engineering:Q4_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf MarshallDoyle/NASA-Systems-Engineering:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf MarshallDoyle/NASA-Systems-Engineering:Q4_K_M
Use Docker
docker model run hf.co/MarshallDoyle/NASA-Systems-Engineering:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use MarshallDoyle/NASA-Systems-Engineering with Ollama:
ollama run hf.co/MarshallDoyle/NASA-Systems-Engineering:Q4_K_M
- Unsloth Studio
How to use MarshallDoyle/NASA-Systems-Engineering with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for MarshallDoyle/NASA-Systems-Engineering to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for MarshallDoyle/NASA-Systems-Engineering to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for MarshallDoyle/NASA-Systems-Engineering to start chatting
- Docker Model Runner
How to use MarshallDoyle/NASA-Systems-Engineering with Docker Model Runner:
docker model run hf.co/MarshallDoyle/NASA-Systems-Engineering:Q4_K_M
- Lemonade
How to use MarshallDoyle/NASA-Systems-Engineering with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull MarshallDoyle/NASA-Systems-Engineering:Q4_K_M
Run and chat with the model
lemonade run user.NASA-Systems-Engineering-Q4_K_M
List all available models
lemonade list
- Atomic Chat
| base_model: unsloth/meta-llama-3.1-8b-instruct-unsloth-bnb-4bit | |
| tags: | |
| - text-generation-inference | |
| - transformers | |
| - llama | |
| - gguf | |
| license: apache-2.0 | |
| language: | |
| - en | |
| # 🚀 NASA Systems Engineering LLaMA-3.1 8B Instruct (Fine-Tuned) | |
| [](https://opensource.org/licenses/Apache-2.0) | |
| [-lightgrey.svg)]() | |
| []() | |
|  | |
| **Developed by:** MarshallDoyle | |
| **Fine-tuned from:** `unsloth/meta-llama-3.1-8b-instruct-unsloth-bnb-4bit` | |
| **Specialization:** NASA *Systems Engineering Handbook* (2018) Q&A | |
| **Training recipe:** LoRA rank=16, epochs=3, steps=285, final loss≈0.40–0.60 | |
| --- | |
| ## ✨ Key Features | |
| | Feature | Details | | |
| |-----------------------|--------------------------------------------------------| | |
| | **Domain Expertise** | Deep knowledge of NASA SE lifecycle, terminology, and best practices. | | |
| | **Compact Footprint** | +83.8M trainable via LoRA on 8B base. | | |
| | **Long Context** | Up to 128K token support for large documents. | | |
| | **Fast Inference** | Efficient TRL & Unsloth pipeline. | | |
| --- | |
| ## 🎯 Intended Use Cases | |
| - **Interactive Q&A:** Rapid lookup of definitions, processes, and phase purposes. | |
| - **Summarization:** Concise overviews of complex sections in the handbook. | |
| - **Educational Tools:** Training aids for systems engineering students and professionals. | |
| - **Mission Planning:** Quick reference for verification, validation, and lifecycle checkpoints. | |
| --- | |
| ## 📊 Example Comparisons | |
| <details> | |
| <summary><strong>Phase C Purpose</strong></summary> | |
| | Model | Response Snippet | | |
| |-------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | |
| | **Base LLaMA-3.1**| _“Phase C covers detailed design and preparations for manufacturing…”_ (generic) | | |
| | **Fine-Tuned** | _“The main purpose is to complete the detailed design of system elements, fabricate hardware, and code software, ensuring all end products are defined for integration.”_ | | |
| </details> | |
| <details> | |
| <summary><strong>Verification vs. Validation</strong></summary> | |
| | Model | Response Snippet | | |
| |-------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | |
| | **Base LLaMA-3.1**| _“Verification checks requirements; validation checks user needs…”_ (too brief) | | |
| | **Fine-Tuned** | _“Verification ensures the system meets specified requirements; validation confirms it satisfies stakeholder expectations in its intended environment.”_ | | |
| </details> | |
| --- | |
| ## ⚠️ Limitations | |
| - **Scope Bounded:** Content based on the 2018 handbook; may omit newer updates. | |
| - **Hallucinations:** Possible on out-of-handbook queries. | |
| - **Bias:** NASA-specific terminology; verify critical engineering decisions against official documents. | |
| --- | |
| 🔗 **Download & Details:** [Hugging Face model page](https://huggingface.co/MarshallDoyle/NASA-Systems-Engineering) | |