Perceiver The Perceiver model was released in the previous version: Perceiver Eight new models are released as part of the Perceiver implementation: PerceiverModel, PerceiverForMaskedLM, PerceiverForSequenceClassification, PerceiverForImageClassificationLearned, PerceiverForImageClassificationFourier, PerceiverForImageClassificationConvProcessing, PerceiverForOpticalFlow, PerceiverForMultimodalAutoencoding, in PyTorch. The Perceiver IO model was proposed in Perceiver IO: A General Architecture for Structured Inputs & Outputs by Andrew Jaegle, Sebastian Borgeaud, Jean-Baptiste Alayrac, Carl Doersch, Catalin Ionescu, David Ding, Skanda Koppula, Daniel Zoran, Andrew Brock, Evan Shelhamer, Olivier Hénaff, Matthew M. Botvinick, Andrew Zisserman,...
FlauBERT, MMBT MMBT was added to the list of available models, as the first multi-modal model to ma...
Transformers: State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX
Name change: welcome Transformers Following the extension to TensorFlow 2.0, pytorch-transformers =...
New model architectures: ALBERT, CamemBERT, GPT2-XL, DistilRoberta Four new models have been added s...
New model architectures: CTRL, DistilGPT-2 Two new models have been added since release 2.0. CTRL (...
New class Pipeline (beta): easily run and use models on down-stream NLP tasks We have added a new cl...
What's Changed Perceiver AR enhancements by @krasserm in https://github.com/krasserm/perceiver-io/p...
New Model: BART (added by @sshleifer) Bart is one of the first Seq2Seq models in the library, and ac...
Add header (huggingface#15434) [Hotfix] Fix Swin model outputs (huggingface#15414) Full Changelog: ...
Transformer, an attention-based encoder-decoder model, has already revolutionized the field of natur...
Transformers: State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch
Better backward-compatibility for tokenizers following v3.0.0 refactoring Version v3.0.0, included a...
Breakthroughs in transformer-based models have revolutionized not only the NLP field, but also visio...
We show how to "compile" human-readable programs into standard decoder-only transformer models. Our ...
Trainer & TFTrainer Version 2.9 introduces a new Trainer class for PyTorch, and its equivalent TFTra...
FlauBERT, MMBT MMBT was added to the list of available models, as the first multi-modal model to ma...
Transformers: State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX
Name change: welcome Transformers Following the extension to TensorFlow 2.0, pytorch-transformers =...
New model architectures: ALBERT, CamemBERT, GPT2-XL, DistilRoberta Four new models have been added s...
New model architectures: CTRL, DistilGPT-2 Two new models have been added since release 2.0. CTRL (...
New class Pipeline (beta): easily run and use models on down-stream NLP tasks We have added a new cl...
What's Changed Perceiver AR enhancements by @krasserm in https://github.com/krasserm/perceiver-io/p...
New Model: BART (added by @sshleifer) Bart is one of the first Seq2Seq models in the library, and ac...
Add header (huggingface#15434) [Hotfix] Fix Swin model outputs (huggingface#15414) Full Changelog: ...
Transformer, an attention-based encoder-decoder model, has already revolutionized the field of natur...
Transformers: State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch
Better backward-compatibility for tokenizers following v3.0.0 refactoring Version v3.0.0, included a...
Breakthroughs in transformer-based models have revolutionized not only the NLP field, but also visio...
We show how to "compile" human-readable programs into standard decoder-only transformer models. Our ...
Trainer & TFTrainer Version 2.9 introduces a new Trainer class for PyTorch, and its equivalent TFTra...
FlauBERT, MMBT MMBT was added to the list of available models, as the first multi-modal model to ma...
Transformers: State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX
Name change: welcome Transformers Following the extension to TensorFlow 2.0, pytorch-transformers =...