Search results
🤗 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 ...
🤗 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.
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.
What is Hugging Face Transformers? Hugging Face Transformers is an open-source Python library that provides access to thousands of pre-trained Transformers models for natural language processing (NLP), computer vision, audio tasks, and more.
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.
Hugging Face transformers is a platform that provides the community with APIs to access and use state-of-the-art pre-trained models available from the Hugging Face hub. What is a pre-trained transformer?
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...
Oct 9, 2019 · Transformer architectures have facilitated building higher-capacity models and pretraining has made it possible to effectively utilize this capacity for a wide variety of tasks. \textit {Transformers} is an open-source library with the goal of opening up these advances to the wider machine learning community.
