Fine-Tuning 101: From LLMs to Embeddings
Join the AI Makerspace team for a workshop on Fine-Tuning 101: From LLMs to Embeddings! They'll demonstrate new capabilities that aspiring AI engineers should be adding to their tool belt.
Most of the time when you’re building LLM applications, you have two places to go for leveraging models: OpenAI and Hugging Face.
While OpenAI models are powerful, easy to use, and can be fine-tuned via their API, Hugging Face provides open-source models that can be leveraged and fine-tuned with some additional setup. Emerging tools like Gradient are now providing a streamlined way to host and fine-tune customized open-source models securely, and access them directly through API endpoints.
In this event, we’ll demonstrate these new capabilities that aspiring AI engineers should be adding to their tool belt with two use cases: 1) an open-source Retrieval Augmented Generation (RAG) system with LangChain and Llama 2, and a fine-tuned embedding model, and 2) fine-tuning the input-output schema of Llama 2.
As always, all concepts and code will be shared live for you to follow along with during the event!
Who should attend the event?
- Aspiring AI Engineers interested in fine-tuning open-source embedding and LLMs.
- Learners who want to understand fine-tuning use-cases.
- Practitioners who want to get hands on with the Gradient developer platform.
Speaker Bio:
- Dr. Greg Loughnane is the Founder & CEO of AI Makerspace, where he serves as an instructor for their LLM Engineering and LLM Ops: LLMs in Production courses. Since 2021 he has built and led industry-leading Machine Learning & AI boot camp programs. Previously, he worked as an AI product manager, a university professor teaching AI, an AI consultant and startup advisor, and ML researcher. He loves trail running and is based in Dayton, Ohio.
- Chris Alexiuk, is the Co-Founder & CTO at AI Makerspace, where he serves as an instructor for their LLM Engineering and LLM Ops: LLMs in Production courses. A former Data Scientist, he also works as the Founding Machine Learning Engineer at Ox. As an experienced online instructor, curriculum developer, and YouTube creator, he’s always learning, building, shipping, and sharing his work! He loves Dungeons & Dragons and is based in Toronto, Canada.
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