Generative AI in Science using Open-Source models
Authors/Creators
Contributors
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Description
Generative AI systems built upon large language models (LLMs) have shown great promise as tools that enable people to access information through natural conversation. Scientists can benefit from the breakthroughs these systems enable to create advanced tools that will help accelerate their research outcomes. This tutorial will cover: (1) the basics of language models, (2) setting up the environment for using open source LLMs without the use of expensive compute resources needed for training or fine-tuning, (3) learning a technique like Retrieval-Augmented Generation (RAG) to optimize output of LLM, and (4) build a “production-ready” app to demonstrate how researchers could turn disparate knowledge bases into special purpose AI-powered tools. The right audience for our tutorial is scientists and research engineers who want to use LLMs for their work.
Files
UW SSEC Gen AI tutorial_ Scipy 2024.pdf
Files
(883.1 kB)
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Additional details
Dates
- Accepted
-
2024-07-09
Software
- Repository URL
- https://uw-ssec-tutorials.readthedocs.io/en/latest/Archive/SciPy2024/README.html
- Programming language
- Python
- Development Status
- Active