One of the top platforms for machine learning (ML) and natural language processing (NLP) is Hugging Face. Building AI-powered apps is made easier by its extensive ecosystem of open-source models, datasets, and tools. Text categorization, translation, summarization, and other cutting-edge NLP tasks are frequently accomplished with its main library, Transformers.
Key Features of Hugging Face
- Pre-trained Models: Thousands of pre-trained models for audio, computer vision, and natural language processing tasks are available.
- Datasets: A library for importing, preparing, and maintaining datasets.
- Tokenizers are effective tokenization tools designed to work with common machine learning architectures.
- Fine-tuning: The ability to modify previously trained models using your own datasets.
How to Use Hugging Face in Python
1. Create an Access Token here
2. Read the instructions in the Model card (model) or Dataset card (dataset)
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