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🤗 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.
State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow. 🤗 Transformers provides thousands of pretrained models to perform tasks on different modalities such as text, vision, and audio. These models can be applied on: 📝 Text, for tasks like text classification, information extraction, question answering, summarization ...
Install 🤗 Transformers for whichever deep learning library you’re working with, setup your cache, and optionally configure 🤗 Transformers to run offline. 🤗 Transformers is tested on Python 3.6+, PyTorch 1.1.0+, TensorFlow 2.0+, and Flax.
🤗 transformers is a library maintained by Hugging Face and the community, for state-of-the-art Machine Learning for Pytorch, TensorFlow and JAX. It provides thousands of pretrained models to perform tasks on different modalities such as text, vision, and audio.
Nov 20, 2023 · Hugging Face Transformers offers cutting-edge machine learning tools for PyTorch, TensorFlow, and JAX. This platform provides easy-to-use APIs and tools for downloading and training top-tier pretrained models.
Installation. You are viewing v4.18.0 version. A newer version v4.42.0 is available. Join the Hugging Face community. and get access to the augmented documentation experience. Collaborate on models, datasets and Spaces. Faster examples with accelerated inference. Switch between documentation themes. to get started. 500.
The Hugging Face Course. This repo contains the content that's used to create the Hugging Face course. The course teaches you about applying Transformers to various tasks in natural language processing and beyond.
Jul 11, 2024 · Transformers is more than a toolkit to use pretrained models: it's a community of projects built around it and the Hugging Face Hub. We want Transformers to enable developers, researchers, students, professors, engineers, and anyone else to build their dream projects.
HuggingFace Models is a prominent platform in the machine learning community, providing an extensive library of pre-trained models for various natural language processing (NLP) tasks. These models are part of the HuggingFace Transformers library, which supports state-of-the-art models like BERT, GPT, T5, and many others.
The pipeline() function from the transformers library can be used to run inference with models from the Hugging Face Hub. This tutorial is based on the first of our O'Reilly book Natural...
