Hugging Face Tutorial for Beginners

Welcome to the Hugging Face course. Hugging Face is a company and open-source community that focuses on natural language processing (NLP) and artificial intelligence (AI). It is best known for its Transformers library, which provides tools and pre-trained models for a wide range of NLP tasks, such as text classification, sentiment analysis, machine translation, and more.

Hugging Face – Features

Here are some of the features of Hugging Face:

• Transformers Library: A comprehensive library that includes thousands of pre-trained models like BERT, GPT, T5, and others, which can be fine-tuned for specific tasks.
• Model Hub: A platform where users can share and download pre-trained models, datasets, and other resources.
• Datasets Library: Provides easy access to a wide variety of datasets for NLP tasks.
• Spaces: A platform for hosting and sharing machine learning demos and applications.
• Inference API: Allows users to deploy and use models in production environments easily.
• Community and Collaboration: Hugging Face fosters a strong community of researchers, developers, and enthusiasts who contribute to the ecosystem.

Hugging Face Overview

1. Hugging Face – Introduction and Features

2. Hugging Face – Use Cases

Hugging Face – Libraries

3. Transformers Library of Hugging Face

4. Datasets Library of Hugging Face

5. Tokenizers Library of Hugging Face

Hugging Face – Access Token (API Key)

6. Hugging Face Access Token (API Key) & How to Create

Working with Datasets and Models

7. Download a dataset on Hugging Face

8. Download a model from Hugging Face

Use Pre-Trained Models with Hugging Face

9. Sentiment Analysis using Hugging Face

10. Text Classification using Hugging Face

11. Text Summarizations using Hugging Face

12. Text to Text (Translate) using Hugging Face

13. Question Answering using Hugging Face

14. Text to Image using Hugging Face

15. Text to Video Synthesis using Hugging Face