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- # Uploaded model
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- - **Developed by:** MarshallDoyle
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- - **License:** apache-2.0
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- - **Finetuned from model :** unsloth/meta-llama-3.1-8b-instruct-unsloth-bnb-4bit
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- This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
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- [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ # NASA Systems Engineering LLaMA-3.1 8B Instruct (Fine-Tuned)
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+ - **Developed by:** MarshallDoyle
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+ - **License:** Apache-2.0
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+ - **Fine-tuned from model:** unsloth/meta-llama-3.1-8b-instruct-unsloth-bnb-4bit
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+ This model specializes in answering questions and summarizing content from NASA’s *Systems Engineering Handbook* (2018) PDF. It was fine-tuned using Hugging Face’s TRL and LoRA techniques for high efficiency.
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+ ## Preview of Fine-Tuning Source
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+ ![Preview of NASA Systems Engineering Handbook first page](https://www.nasa.gov/sites/default/files/atoms/files/nasa_systems_engineering_handbook_0.pdf#page=1)
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+ *(Above: the front page of the NASA Systems Engineering Handbook used for fine-tuning.)*
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+ ---
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+ ## Overview
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+ **Key Features:**
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+ - **Domain Expertise:** Deep understanding of NASA systems engineering lifecycle phases, verification vs. validation testing, and SE best practices.
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+ - **Compact Footprint:** Keeps the lightweight 8B base model, adding only ~83.8M trainable parameters via LoRA.
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+ - **Extended Context:** Supports up to 128K tokens for long-form document Q&A.
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+ **Intended Use:** Ideal for educational tools, engineering Q&A assistants, mission planning support, and rapid handbook lookup.
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+ ---
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+ ## Model Card Updates
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+ - Removed Unsloth branding badges in favor of a direct preview of the NASA PDF source.
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+ - Added a representative image of the handbook’s first page to illustrate the training data.
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+ ---
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+ *