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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.
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.
The course teaches you about applying Transformers to various tasks in natural language processing and beyond. Along the way, you'll learn how to use the Hugging Face ecosystem — 🤗 Transformers, 🤗 Datasets, 🤗 Tokenizers, and 🤗 Accelerate — as well as the Hugging Face Hub. It's completely free and open-source!
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.
An Introduction to Using Transformers and Hugging Face. Understand Transformers and harness their power to solve real-life problems. Aug 2022 · 15 min read. Introduction. The extensive contribution of researchers in NLP, short for Natural Language Processing, during the last decades has been generating innovative results in different domains.
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX. - huggingface/transformers
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...
🤗 Transformers State-of-the-art Machine Learning for PyTorch, TensorFlow and JAX. 🤗 Transformers provides APIs to easily download and train state-of-the-art pretrained models. Using pretrained models can reduce your compute costs, carbon footprint, and save you time from training a model from scratch.
