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Transformers Library

The Transformers library is an open-source Python library developed by Hugging Face that provides state-of-the-art pre-trained models for natural language processing (NLP) and computer vision tasks. It offers a unified API for accessing and fine-tuning transformer-based models like BERT, GPT, and T5, enabling developers to easily implement tasks such as text classification, translation, and question answering. The library supports thousands of models and includes tools for training, evaluation, and deployment across various frameworks like PyTorch, TensorFlow, and JAX.

Also known as: Hugging Face Transformers, Transformers by Hugging Face, HF Transformers, Transformers (Hugging Face), HuggingFace Transformers
🧊Why learn Transformers Library?

Developers should learn and use the Transformers library when working on NLP or multimodal AI projects that require leveraging pre-trained models for efficiency and performance. It is particularly valuable for applications like chatbots, sentiment analysis, document summarization, and image captioning, as it reduces the need for training models from scratch and provides access to cutting-edge architectures. The library's extensive model hub and community support make it ideal for both research and production environments in machine learning.

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