Offered By: IBMSkillsNetwork
Fine-Tuning Large Language Models with DPO & Hugging Face
Explore Direct Preference Optimization (DPO) with Hugging Face and trl libraries in this guided project designed to fine-tune LLMs. Participants will learn to align large language models with user preferences by implementing DPO and preprocessing data sets of categorized news articles. The project provides hands-on experience in model training and performance evaluation, and it explains the distinctions between DPO and other techniques, such as proximal policy optimization.
Continue readingGuided Project
Artificial Intelligence
At a Glance
Explore Direct Preference Optimization (DPO) with Hugging Face and trl libraries in this guided project designed to fine-tune LLMs. Participants will learn to align large language models with user preferences by implementing DPO and preprocessing data sets of categorized news articles. The project provides hands-on experience in model training and performance evaluation, and it explains the distinctions between DPO and other techniques, such as proximal policy optimization.
Through this hands-on experience, participants will implement DPO, preprocess datasets, and gain insights into the intricacies of model training and performance evaluation. Furthermore, learners will differentiate DPO from other techniques, such as proximal policy optimization, thereby expanding their expertise in NLP applications. This project caters to intermediate-level practitioners eager to deepen their understanding of preference-based model optimization and its practical applications.
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What You'll Learn
- Acquire a comprehensive understanding of Direct Preference Optimization and its role in fine-tuning language models.
- Master the use of Hugging Face and trl libraries for effective model training and evaluation.
- Develop the skills to preprocess and categorize news article datasets for aligning models with user preferences.
- Differentiate between DPO and other optimization techniques, thereby enhancing comparative analysis skills in NLP model training.
What You'll Need
- Intermediate proficiency in Python programming.
- Familiarity with fundamental NLP concepts.
- A basic understanding of machine learning model training principles.
- Access to a compatible web browser: Chrome, Edge, Firefox, Internet Explorer, or Safari, to ensure optimal performance in the IBM Skills Network Labs environment.
Who Should Complete This Project?
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Embark on this insightful journey into Direct Preference Optimization and elevate your expertise in natural language processing. Enroll now to unlock the potential of aligning language models with user preferences and position yourself at the forefront of NLP innovation.
Estimated Effort
40 Minutes
Level
Intermediate
Skills You Will Learn
Artificial Intelligence, HuggingFace, LLM, NLP
Language
English
Course Code
GPXX0CZUEN