Hugging Face

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


What you'll learn
Grasp the core concepts of the Hugging Face ecosystem
Learn how to prepare datasets and fine-tune pretrained models for specific tasks,
Complete a case study to manage a project from conception to completion, utilizing Hugging Face resources to build
Gain the skills to implement real-world applications using Hugging Face models and pipelines, including creating and deploying NLP

Requirements
Basic Python Programming Skills:
Familiarity with Python syntax and basic programming concepts.
Understanding of Machine Learning Concepts:
Basic knowledge of machine learning principles and algorithms.

Description
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:
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.
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.
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.
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.
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.
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.
Who this course is for:
Data Scientists and Machine Learning Engineers
Business Analysts and Data Analysts
Product Managers and Technical Leaders
Students and Graduates

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