Hugging Face | Udemy


Hugging Face | Udemy [Update 01/2024]
English | Size: 1.2 GB
Genre: eLearning

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

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.

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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