Fine-Tuning LLMs: Best Practices and When to Go Small

Name: Fine-Tuning LLMs: Best Practices and When to Go Small
Uploaded: 2023-06-01
Description: With the open source releasing foundational models at a blistering pace there has never been a better time to develop an AI-powered product. In this talk, we walk you through the challenges and state-of-the-art techniques that can help you fine-tune your own LLMs. Additionally, we will provide guidance on how to determine when a small model would be more appropriate for your use case.

Posted Jun 01, 2023 | Views 1.6K

# Large Language Models

# LLM

# AI-powered Product

# Preemo

# Gradient.ai

SPEAKER

Mark Huang

Co-Founder @ Gradient

Mark is a co-founder and Chief Architect at Gradient, a platform that helps companies build custom AI applications by making it extremely easy to fine-tune foundational models and deploy them into production. Previously, he was a tech lead in machine learning teams at Splunk and Box, developing and deploying production systems for streaming analytics, personalization, and forecasting. Prior to his career in software development, he was an algorithmic trader at quantitative hedge funds where he also harnessed large-scale data to generate trading signals for billion-dollar asset portfolios.

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SUMMARY

With the open source releasing foundational models at a blistering pace there has never been a better time to develop an AI-powered product. In this talk, we walk you through the challenges and state-of-the-art techniques that can help you fine-tune your own LLMs. Additionally, we will provide guidance on how to determine when a small model would be more appropriate for your use case.

+ Read More

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