Hugging Face for Beginners

Welcome to the Hugging Face course. Hugging Face is an open-source organization and company dedicated to natural language processing (NLP) and artificial intelligence (AI). It is most famous for its Transformers library, which offers pre-trained models and tools for most NLP tasks, including text classification, sentiment analysis, machine translation, and so on.

Hugging Face – Features
Some of the characteristics of Hugging Face are:
Transformers Library: A library with thousands of pre-trained models like BERT, GPT, T5, and so on, that can be fine-tuned for a specific task.
Model Hub: A location in which users are able to upload and download pre-trained models, data sets, and other assets.
Datasets Library: Offers easy access to a large range of datasets for NLP tasks.
Spaces: A space for hosting and sharing machine learning demos and applications.
Inference API: Allows simple deployment and usage in production.
Community and Collaboration: Hugging Face has a vast community of developers, researchers, and enthusiasts contributing to the platform.
1. Hugging Face - Introduction and Features
2. Hugging Face - Use Cases
3. Transformers Library of Hugging Face
4. Datasets Library of Hugging Face
5. Tokenizers Library of Hugging Face
6. Hugging Face Access Token (API Key) & How to Create
7. Download a dataset on Hugging Face
8. Load a model from 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) with Hugging Face
13. Question Answering with Hugging Face
14. Text to Image from Hugging Face
15. Text to Video Synthesis from Hugging Face