Making LLM fine-tuning accessible with InstructLab
Ravindra Patil, Dasharath Masirkar, Cedric Clyburn, Presha Pathak, Shardul Inamdar
The rise of large language models (LLMs) has opened up exciting possibilities for developers looking to build intelligent applications. However, the process of adapting these models to specific use cases can be difficult, requiring deep expertise and substantial resources. In this talk, we'll introduce you to InstructLab, an open-source project that aims to make LLM tuning accessible to developers and engineers of all skill levels, on consumer-grade hardware.
We'll explore how InstructLab's innovative approach combines collaborative knowledge curation, efficient data generation, and instruction training to enable developers to refine foundation models for specific use cases. In this workshop, you’ll be provided a RHEL VM and learn how to enhance an LLM with new knowledge and capabilities for targeted applications, without needing data science expertise. Join us to explore how LLM tuning can be more accessible and democratized, empowering developers to build on the power of AI in their projects.
AI, Data Science, and Emerging Tech
Workshops (School of Design)