Language: English (US)

Hugging Face - 15% theory 85% hands-on Lab

https://www.udemy.com/course/hugging-face-15-theory-85-hands-on-lab/

Welcome to "Hugging Face with Fine-Tune LLM," a comprehensive course designed to empower you with the skills and knowledge needed to harness the power of Hugging Face’s cutting-edge NLP tools and techniques. This course will take you through the essentials of working with large language models (LLMs) and guide you in fine-tuning them for various natural language processing tasks.

What You'll Learn:

1. Fundamentals of Hugging Face:

   • Gain a solid understanding of the Hugging Face ecosystem and its significance in the field of NLP.

   • Learn to navigate and utilize the Hugging Face Transformers library effectively.

2. Working with Pre-trained Models:

   • Explore the architecture and applications of popular models like BERT, GPT, and T5.

   • Learn to load and deploy pre-trained models for tasks such as text classification, named entity recognition, and text generation.

3. Fine-Tuning Large Language Models:

   • Understand the process of preparing datasets for fine-tuning.

   • Master the techniques for fine-tuning models on custom datasets to achieve high accuracy and performance.

4. Model Evaluation and Optimization:

   • Discover methods to evaluate the performance of your models using appropriate metrics.

   • Learn to interpret results and optimize models for better efficiency and accuracy.

5. Advanced Techniques and Deployment:

   • Delve into advanced techniques like model distillation, quantization, and pruning.

   • Gain insights into deploying models using Hugging Face’s Inference API and other strategies to bring your NLP solutions to production.

6. Hands-On Projects and Case Studies:

   • Engage in real-world projects that reinforce your learning and provide practical experience.

   • Analyze case studies to understand the application of best practices in various NLP scenarios.

Who Should Enroll:

This course is ideal for:

• Data Scientists and Machine Learning Engineers seeking to deepen their expertise in NLP.

• Software Developers interested in integrating NLP features into their applications.

• Researchers and Academicians aiming to apply advanced NLP techniques in their work.