Hands-On Hugging Face Tutorial | Transformers, AI Pipeline, Fine Tuning LLM, GPT, Sentiment Analysis

Want to Learn Building AI Agents? 👉 https://www.maryammiradi.com/ai-agents-mastery ︾︾︾︾︾︾︾︾︾︾︾︾︾︾︾︾︾︾︾︾ This video: 🔰 This hands-on LLM tutorial will get you up and running with Hugging Face in no time. ︾︾︾︾︾︾︾︾︾︾︾︾︾︾︾︾︾︾︾︾ This is the 1st video in a series on using large language models (LLMs) in practice. This comprehensive HuggingFace tutorial covers the installation and use of the Transformer Python Library, using Pipelines for Sentiment analysis, Text classification, Text generation, and Question answering, as well as fine tuning LLMs. You will learn how to effectively use Hugging Face Spaces and Models for NLP projects, including how to use huggingface models like GPT and BERT with Tokenization. By the end, you'll be equipped with the skills to handle data science projects with Hugging Face, leverage AI models from Hugging Face transformers to apply powerful LLM models from OpenAI, Llama 3, and more, and use the arXiv API to pull data from 2.4 million academic papers and summarize them. ⏰ Timecodes ⏰ 0:00 Intro to Hugging Face and its importance to NLP Projects and LLM 0:42 - Installing the Transformer Python Library of Huggingface 0:50 - Setting Up Hugging Face Pipelines 1:12 - Navigating Hugging Face Hub NLP Tasks 2:15 - Sentiment Analysis with Hugging Face 5:48 - Get Free Data Science, Machine Learning and Deep Learning Guide 6:00 - Text Generation with Hugging Face - Natural Language processing 6:45 - Question Answering with Hugging Face 7:12 - Tokenization with Models like GPT and BERT 9:47 - Fine Tuning LLM using hugging face AI Train 12:38 - Hugging Face Spaces 13:10 - Text summarization NLP Project using arXiv API using arxiv research papers 14:35 - AI apps for Text data #huggingface #llm #finetuning #sentimentanalysis #gpt #ai #python #datascience #datasciencetutorial #datascienceprojects #langchain #openaichatbotgpt #largelanguagemodels #openai #tutorial #stepbystep #artificialintelligence