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  3. Transformers
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Transformers

Hugging Face Transformers provides APIs/tools to easily download and train state-of-the-art pretrained models for PyTorch, TensorFlow, and JAX.

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Introduction

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Information

  • Publisher
    Jeremy Xiao
  • Websitehuggingface.co
  • Published date2025/02/28

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  • Science
  • Coding
  • Research

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  • github
  • open source

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    πŸ€— Transformers

    State-of-the-art Machine Learning for PyTorch, TensorFlow, and JAX.

    πŸ€— Transformers provides APIs and tools to easily download and train state-of-the-art pretrained models. Using pretrained models can reduce your compute costs, carbon footprint, and save you the time and resources required to train a model from scratch. These models support common tasks in different modalities, such as:

    πŸ“ Natural Language Processing: text classification, named entity recognition, question answering, language modeling, code generation, summarization, translation, multiple choice, and text generation.

    πŸ–ΌοΈ Computer Vision: image classification, object detection, and segmentation.

    πŸ—£οΈ Audio: automatic speech recognition and audio classification.

    πŸ™ Multimodal: table question answering, optical character recognition, information extraction from scanned documents, video classification, and visual question answering.

    πŸ€— Transformers support framework interoperability between PyTorch, TensorFlow, and JAX. This provides the flexibility to use a different framework at each stage of a model’s life; train a model in three lines of code in one framework, and load it for inference in another. Models can also be exported to a format like ONNX and TorchScript for deployment in production environments.

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