Free Download Hugging Face
Published 6/2024
Created by Anil Bidari
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 12 Lectures ( 1h 18m ) | Size: 1.23 GB
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
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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