Fine-Tuning Transformers with Hugging Face

Master the complete workflow for fine-tuning transformer models using the Hugging Face ecosystem. This hands-on course takes you from navigating the Hugging Face Hub to deploying production-ready models.You'll start by learning to discover, evaluate, and select models and datasets from the Hub's vast repository. Then you'll build practical skills in loading and preprocessing data, including streaming techniques for datasets too large to fit in memory.The core of the course focuses on fine-tuning transformers using the Trainer API. You'll implement custom callbacks, configure training optimizations like mixed precision, and develop comprehensive evaluation pipelines with metrics including accuracy, F1, precision, and recall.The capstone project ties everything together: you'll build an end-to-end sentiment analysis system, from data preprocessing and augmentation through training, evaluation, and publishing your model to Hugging Face Hub with professional documentation.By course end, you'll have hands-on experience with the same tools and workflows used by ML teams at leading organizations, plus a published model in your portfolio

• Navigate the Hugging Face Hub to discover, evaluate, and select models and datasets based on task requirements, licensing, and technical constraints
• Master the complete workflow for fine-tuning transformer models using the Hugging Face ecosystem
• Apply efficient data loading and preprocessing techniques including streaming for large datasets
• Develop custom callbacks and configure training optimizations such as mixed precision
• Build comprehensive evaluation pipelines using accuracy, F1 score, precision, and recall metrics

• Basic familiarity with the topic and its common terminology
• Readiness to practice through applied exercises or case-based work