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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.
- Graphormer
Our key insight to utilizing Transformer in the graph is the...
- Clip
CLIP uses a ViT like transformer to get visual features and...
- MatCha
MatCha Overview. MatCha has been proposed in the paper...
- OneFormer
OneFormer Overview. The OneFormer model was proposed in...
- Graphormer
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 ...
Nov 20, 2023 · Hugging Face Transformers provides easy-to-use APIs and tools for downloading and training pretrained models for various tasks across different modalities. It also supports framework interoperability and model deployment in PyTorch, TensorFlow, JAX, and other formats.
Try out different transformer models for text generation, such as GPT-2, XLNet, GPT and DistilGPT-2. See how a neural network can complete your sentences and write papers on NLP topics.
Browse and explore hundreds of transformer models for various natural language processing tasks. Find the latest and most popular models by authors, categories, and metrics.
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.
Learn how to apply Transformers to natural language processing and beyond with this free and open-source course. Find the content, translations, and instructions for contributing to the course on GitHub.
