HuggingFace is an open AI community that promotes open-source contributions, serving as a hub for natural language processing, computer vision, and other areas where AI plays a significant role. Even tech giants like Google, Facebook, AWS, Microsoft, and others utilize the models, datasets, and libraries.
Hugging Face offers state-of-the-art models for various tasks, providing a vast array of pre-trained models for different purposes. At the time of writing this article (March 2023), there were over 150,000 pre-trained models available. HuggingFace supports the following tasks:
- Text classification
- Text generation
- Translation
- Summarization
- Mask filling
- Question-answering
- Zero-shot classification
- Sentence similarity
- Image classification
- Image segmentation
- Object detection
- Voice recognition
- Voice synthesis
- Automatic speech recognition
- Audio classification
There are more than 25,000 datasets present in the HuggingFace Dataset collection at the time of writing this article. These datasets are available in multiple languages to aid in training our models or refining them using these datasets.
HuggingFace’s Datasets library provides the ability to load these datasets, as well as our own. The library also offers commonly used operations for processing datasets, including shuffling, sampling, filtering, and more. With the assistance of Apache Arrow, this library enables us to work with datasets larger than our memory capacity.
