600 Repositories
Python onnx-transformers Libraries
Generate indoor scenes with Transformers
SceneFormer: Indoor Scene Generation with Transformers Initial code release for the Sceneformer paper, contains models, train and test scripts for the
CoaT: Co-Scale Conv-Attentional Image Transformers
CoaT: Co-Scale Conv-Attentional Image Transformers Introduction This repository contains the official code and pretrained models for CoaT: Co-Scale Co
VideoGPT: Video Generation using VQ-VAE and Transformers
VideoGPT: Video Generation using VQ-VAE and Transformers [Paper][Website][Colab][Gradio Demo] We present VideoGPT: a conceptually simple architecture
[Preprint] Escaping the Big Data Paradigm with Compact Transformers, 2021
Compact Transformers Preprint Link: Escaping the Big Data Paradigm with Compact Transformers By Ali Hassani[1]*, Steven Walton[1]*, Nikhil Shah[1], Ab
[CVPR'21] Multi-Modal Fusion Transformer for End-to-End Autonomous Driving
TransFuser This repository contains the code for the CVPR 2021 paper Multi-Modal Fusion Transformer for End-to-End Autonomous Driving. If you find our
Implementation of Perceiver, General Perception with Iterative Attention in TensorFlow
Perceiver This Python package implements Perceiver: General Perception with Iterative Attention by Andrew Jaegle in TensorFlow. This model builds on t
PRTR: Pose Recognition with Cascade Transformers
PRTR: Pose Recognition with Cascade Transformers Introduction This repository is the official implementation for Pose Recognition with Cascade Transfo
Changing the Mind of Transformers for Topically-Controllable Language Generation
We will first introduce the how to run the IPython notebook demo by downloading our pretrained models. Then, we will introduce how to run our training and evaluation code.
Implementation of Cross Transformer for spatially-aware few-shot transfer, in Pytorch
Cross Transformers - Pytorch (wip) Implementation of Cross Transformer for spatially-aware few-shot transfer, in Pytorch Install $ pip install cross-t
Implementation of TransGanFormer, an all-attention GAN that combines the finding from the recent GanFormer and TransGan paper
TransGanFormer (wip) Implementation of TransGanFormer, an all-attention GAN that combines the finding from the recent GansFormer and TransGan paper. I
The source code for the Cutoff data augmentation approach proposed in this paper: "A Simple but Tough-to-Beat Data Augmentation Approach for Natural Language Understanding and Generation".
Cutoff: A Simple Data Augmentation Approach for Natural Language This repository contains source code necessary to reproduce the results presented in
Official repository for "PAIR: Planning and Iterative Refinement in Pre-trained Transformers for Long Text Generation"
pair-emnlp2020 Official repository for the paper: Xinyu Hua and Lu Wang: PAIR: Planning and Iterative Refinement in Pre-trained Transformers for Long
Implementation of various Vision Transformers I found interesting
Implementation of various Vision Transformers I found interesting
Code for "LoFTR: Detector-Free Local Feature Matching with Transformers", CVPR 2021
LoFTR: Detector-Free Local Feature Matching with Transformers Project Page | Paper LoFTR: Detector-Free Local Feature Matching with Transformers Jiami
[CVPR 2021] Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers
[CVPR 2021] Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers
Top2Vec is an algorithm for topic modeling and semantic search.
Top2Vec is an algorithm for topic modeling and semantic search. It automatically detects topics present in text and generates jointly embedded topic, document and word vectors.
《LXMERT: Learning Cross-Modality Encoder Representations from Transformers》(EMNLP 2020)
The Most Important Thing. Our code is developed based on: LXMERT: Learning Cross-Modality Encoder Representations from Transformers
Group-Free 3D Object Detection via Transformers
Group-Free 3D Object Detection via Transformers By Ze Liu, Zheng Zhang, Yue Cao, Han Hu, Xin Tong. This repo is the official implementation of "Group-
source code and pre-trained/fine-tuned checkpoint for NAACL 2021 paper LightningDOT
LightningDOT: Pre-training Visual-Semantic Embeddings for Real-Time Image-Text Retrieval This repository contains source code and pre-trained/fine-tun
Code for CVPR 2021 paper: Revamping Cross-Modal Recipe Retrieval with Hierarchical Transformers and Self-supervised Learning
Revamping Cross-Modal Recipe Retrieval with Hierarchical Transformers and Self-supervised Learning This is the PyTorch companion code for the paper: A
Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA.
PyTorch Implementation of Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers 1 Using Colab Please notic
Implementation of the paper "Language-agnostic representation learning of source code from structure and context".
Code Transformer This is an official PyTorch implementation of the CodeTransformer model proposed in: D. Zügner, T. Kirschstein, M. Catasta, J. Leskov
PyTorch Implementation of CvT: Introducing Convolutions to Vision Transformers
CvT: Introducing Convolutions to Vision Transformers Pytorch implementation of CvT: Introducing Convolutions to Vision Transformers Usage: img = torch
Guide: Finetune GPT2-XL (1.5 Billion Parameters) and GPT-NEO (2.7 B) on a single 16 GB VRAM V100 Google Cloud instance with Huggingface Transformers using DeepSpeed
Guide: Finetune GPT2-XL (1.5 Billion Parameters) and GPT-NEO (2.7 Billion Parameters) on a single 16 GB VRAM V100 Google Cloud instance with Huggingfa
Implementation of STAM (Space Time Attention Model), a pure and simple attention model that reaches SOTA for video classification
STAM - Pytorch Implementation of STAM (Space Time Attention Model), yet another pure and simple SOTA attention model that bests all previous models in
The project is an official implementation of our paper "3D Human Pose Estimation with Spatial and Temporal Transformers".
3D Human Pose Estimation with Spatial and Temporal Transformers This repo is the official implementation for 3D Human Pose Estimation with Spatial and
Code for Transformers Solve Limited Receptive Field for Monocular Depth Prediction
Official PyTorch code for Transformers Solve Limited Receptive Field for Monocular Depth Prediction. Guanglei Yang, Hao Tang, Mingli Ding, Nicu Sebe,
An implementation of Performer, a linear attention-based transformer, in Pytorch
Performer - Pytorch An implementation of Performer, a linear attention-based transformer variant with a Fast Attention Via positive Orthogonal Random
Pretrained EfficientNet, EfficientNet-Lite, MixNet, MobileNetV3 / V2, MNASNet A1 and B1, FBNet, Single-Path NAS
(Generic) EfficientNets for PyTorch A 'generic' implementation of EfficientNet, MixNet, MobileNetV3, etc. that covers most of the compute/parameter ef
Reformer, the efficient Transformer, in Pytorch
Reformer, the Efficient Transformer, in Pytorch This is a Pytorch implementation of Reformer https://openreview.net/pdf?id=rkgNKkHtvB It includes LSH
An easier way to build neural search on the cloud
An easier way to build neural search on the cloud Jina is a deep learning-powered search framework for building cross-/multi-modal search systems (e.g
Dense Prediction Transformers
Vision Transformers for Dense Prediction This repository contains code and models for our paper: Vision Transformers for Dense Prediction René Ranftl,
BossNAS: Exploring Hybrid CNN-transformers with Block-wisely Self-supervised Neural Architecture Search
BossNAS This repository contains PyTorch evaluation code, retraining code and pretrained models of our paper: BossNAS: Exploring Hybrid CNN-transforme
⚡ boost inference speed of T5 models by 5x & reduce the model size by 3x using fastT5.
Reduce T5 model size by 3X and increase the inference speed up to 5X. Install Usage Details Functionalities Benchmarks Onnx model Quantized onnx model
Adaptive Attention Span for Reinforcement Learning
Adaptive Transformers in RL Official implementation of Adaptive Transformers in RL In this work we replicate several results from Stabilizing Transfor
A deep learning-based translation library built on Huggingface transformers
DL Translate A deep learning-based translation library built on Huggingface transformers and Facebook's mBART-Large 💻 GitHub Repository 📚 Documentat
Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch
Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch
Simple command line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network)
Simple command line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network)
Model parallel transformers in Jax and Haiku
Mesh Transformer Jax A haiku library using the new(ly documented) xmap operator in Jax for model parallelism of transformers. See enwik8_example.py fo
[CVPR2021 Oral] End-to-End Video Instance Segmentation with Transformers
VisTR: End-to-End Video Instance Segmentation with Transformers This is the official implementation of the VisTR paper: Installation We provide instru
Official codebase for Pretrained Transformers as Universal Computation Engines.
universal-computation Overview Official codebase for Pretrained Transformers as Universal Computation Engines. Contains demo notebook and scripts to r
[CVPR2021 Oral] UP-DETR: Unsupervised Pre-training for Object Detection with Transformers
UP-DETR: Unsupervised Pre-training for Object Detection with Transformers This is the official PyTorch implementation and models for UP-DETR paper: @a
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
MMdnn MMdnn is a comprehensive and cross-framework tool to convert, visualize and diagnose deep learning (DL) models. The "MM" stands for model manage
Open standard for machine learning interoperability
Open Neural Network Exchange (ONNX) is an open ecosystem that empowers AI developers to choose the right tools as their project evolves. ONNX provides
Universal 1d/2d data containers with Transformers functionality for data analysis.
XPandas (extended Pandas) implements 1D and 2D data containers for storing type-heterogeneous tabular data of any type, and encapsulates feature extra
Visualizer for neural network, deep learning, and machine learning models
Netron is a viewer for neural network, deep learning and machine learning models. Netron supports ONNX (.onnx, .pb, .pbtxt), Keras (.h5, .keras), Tens
Implementation of COCO-LM, Correcting and Contrasting Text Sequences for Language Model Pretraining, in Pytorch
COCO LM Pretraining (wip) Implementation of COCO-LM, Correcting and Contrasting Text Sequences for Language Model Pretraining, in Pytorch. They were a
Implementation of OmniNet, Omnidirectional Representations from Transformers, in Pytorch
Omninet - Pytorch Implementation of OmniNet, Omnidirectional Representations from Transformers, in Pytorch. The authors propose that we should be atte
GANsformer: Generative Adversarial Transformers Drew A
GANsformer: Generative Adversarial Transformers Drew A. Hudson* & C. Lawrence Zitnick *I wish to thank Christopher D. Manning for the fruitf
Implementation of Transformer in Transformer, pixel level attention paired with patch level attention for image classification, in Pytorch
Transformer in Transformer Implementation of Transformer in Transformer, pixel level attention paired with patch level attention for image c
Pytorch Code for "Medical Transformer: Gated Axial-Attention for Medical Image Segmentation"
Medical-Transformer Pytorch Code for the paper "Medical Transformer: Gated Axial-Attention for Medical Image Segmentation" About this repo: This repo
Implementation of SETR model, Original paper: Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers.
SETR - Pytorch Since the original paper (Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers.) has no official
This repo holds code for TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation
TransUNet This repo holds code for TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation Usage
Implementation of TimeSformer, a pure attention-based solution for video classification
TimeSformer - Pytorch Implementation of TimeSformer, a pure and simple attention-based solution for reaching SOTA on video classification.
Implementation of self-attention mechanisms for general purpose. Focused on computer vision modules. Ongoing repository.
Self-attention building blocks for computer vision applications in PyTorch Implementation of self attention mechanisms for computer vision in PyTorch
Summarization, translation, sentiment-analysis, text-generation and more at blazing speed using a T5 version implemented in ONNX.
Summarization, translation, Q&A, text generation and more at blazing speed using a T5 version implemented in ONNX. This package is still in alpha stag
Translate - a PyTorch Language Library
NOTE PyTorch Translate is now deprecated, please use fairseq instead. Translate - a PyTorch Language Library Translate is a library for machine transl
spaCy plugin for Transformers , Udify, ELmo, etc.
Camphr - spaCy plugin for Transformers, Udify, Elmo, etc. Camphr is a Natural Language Processing library that helps in seamless integration for a wid
A model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing neural networks
A Deep Learning NLP/NLU library by Intel® AI Lab Overview | Models | Installation | Examples | Documentation | Tutorials | Contributing NLP Architect
Super easy library for BERT based NLP models
Fast-Bert New - Learning Rate Finder for Text Classification Training (borrowed with thanks from https://github.com/davidtvs/pytorch-lr-finder) Suppor
🛸 Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy
spacy-transformers: Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy This package provides spaCy components and architectures to use tr
:mag: End-to-End Framework for building natural language search interfaces to data by utilizing Transformers and the State-of-the-Art of NLP. Supporting DPR, Elasticsearch, HuggingFace’s Modelhub and much more!
Haystack is an end-to-end framework that enables you to build powerful and production-ready pipelines for different search use cases. Whether you want
State of the Art Natural Language Processing
Spark NLP: State of the Art Natural Language Processing Spark NLP is a Natural Language Processing library built on top of Apache Spark ML. It provide
An easier way to build neural search on the cloud
An easier way to build neural search on the cloud Jina is a deep learning-powered search framework for building cross-/multi-modal search systems (e.g
Sentence Embeddings with BERT & XLNet
Sentence Transformers: Multilingual Sentence Embeddings using BERT / RoBERTa / XLM-RoBERTa & Co. with PyTorch This framework provides an easy method t
💥 Fast State-of-the-Art Tokenizers optimized for Research and Production
Provides an implementation of today's most used tokenizers, with a focus on performance and versatility. Main features: Train new vocabularies and tok
🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.
State-of-the-art Natural Language Processing for PyTorch and TensorFlow 2.0 🤗 Transformers provides thousands of pretrained models to perform tasks o
TransGAN: Two Transformers Can Make One Strong GAN
[Preprint] "TransGAN: Two Transformers Can Make One Strong GAN", Yifan Jiang, Shiyu Chang, Zhangyang Wang
Summarization, translation, sentiment-analysis, text-generation and more at blazing speed using a T5 version implemented in ONNX.
Summarization, translation, Q&A, text generation and more at blazing speed using a T5 version implemented in ONNX. This package is still in alpha stag
Translate - a PyTorch Language Library
NOTE PyTorch Translate is now deprecated, please use fairseq instead. Translate - a PyTorch Language Library Translate is a library for machine transl
spaCy plugin for Transformers , Udify, ELmo, etc.
Camphr - spaCy plugin for Transformers, Udify, Elmo, etc. Camphr is a Natural Language Processing library that helps in seamless integration for a wid
A model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing neural networks
A Deep Learning NLP/NLU library by Intel® AI Lab Overview | Models | Installation | Examples | Documentation | Tutorials | Contributing NLP Architect
Super easy library for BERT based NLP models
Fast-Bert New - Learning Rate Finder for Text Classification Training (borrowed with thanks from https://github.com/davidtvs/pytorch-lr-finder) Suppor
🛸 Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy
spacy-transformers: Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy This package provides spaCy components and architectures to use tr
:mag: Transformers at scale for question answering & neural search. Using NLP via a modular Retriever-Reader-Pipeline. Supporting DPR, Elasticsearch, HuggingFace's Modelhub...
Haystack is an end-to-end framework for Question Answering & Neural search that enables you to ... ... ask questions in natural language and find gran
State of the Art Natural Language Processing
Spark NLP: State of the Art Natural Language Processing Spark NLP is a Natural Language Processing library built on top of Apache Spark ML. It provide
An easier way to build neural search on the cloud
An easier way to build neural search on the cloud Jina is a deep learning-powered search framework for building cross-/multi-modal search systems (e.g
Sentence Embeddings with BERT & XLNet
Sentence Transformers: Multilingual Sentence Embeddings using BERT / RoBERTa / XLM-RoBERTa & Co. with PyTorch This framework provides an easy method t
💥 Fast State-of-the-Art Tokenizers optimized for Research and Production
Provides an implementation of today's most used tokenizers, with a focus on performance and versatility. Main features: Train new vocabularies and tok
🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.
State-of-the-art Natural Language Processing for PyTorch and TensorFlow 2.0 🤗 Transformers provides thousands of pretrained models to perform tasks o
Machine learning framework for both deep learning and traditional algorithms
NeoML is an end-to-end machine learning framework that allows you to build, train, and deploy ML models. This framework is used by ABBYY engineers for
Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch
DALL-E in Pytorch Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch. It will also contain CLIP for ranking the ge
DeiT: Data-efficient Image Transformers
DeiT: Data-efficient Image Transformers This repository contains PyTorch evaluation code, training code and pretrained models for DeiT (Data-Efficient
Implementation of Bottleneck Transformer in Pytorch
Bottleneck Transformer - Pytorch Implementation of Bottleneck Transformer, SotA visual recognition model with convolution + attention that outperforms
An implementation of model parallel GPT-3-like models on GPUs, based on the DeepSpeed library. Designed to be able to train models in the hundreds of billions of parameters or larger.
GPT-NeoX An implementation of model parallel GPT-3-like models on GPUs, based on the DeepSpeed library. Designed to be able to train models in the hun
Open-AI's DALL-E for large scale training in mesh-tensorflow.
DALL-E in Mesh-Tensorflow [WIP] Open-AI's DALL-E in Mesh-Tensorflow. If this is similarly efficient to GPT-Neo, this repo should be able to train mode
Simple command line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network)
Deep Daze mist over green hills shattered plates on the grass cosmic love and attention a time traveler in the crowd life during the plague meditative
Graph Transformer Architecture. Source code for
Graph Transformer Architecture Source code for the paper "A Generalization of Transformer Networks to Graphs" by Vijay Prakash Dwivedi and Xavier Bres
Big Bird: Transformers for Longer Sequences
BigBird, is a sparse-attention based transformer which extends Transformer based models, such as BERT to much longer sequences. Moreover, BigBird comes along with a theoretical understanding of the capabilities of a complete transformer that the sparse model can handle.
Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers
Segmentation Transformer Implementation of Segmentation Transformer in PyTorch, a new model to achieve SOTA in semantic segmentation while using trans
Bottleneck Transformers for Visual Recognition
Bottleneck Transformers for Visual Recognition Experiments Model Params (M) Acc (%) ResNet50 baseline (ref) 23.5M 93.62 BoTNet-50 18.8M 95.11% BoTNet-
Explainability for Vision Transformers (in PyTorch)
Explainability for Vision Transformers (in PyTorch) This repository implements methods for explainability in Vision Transformers
Implementation of SE3-Transformers for Equivariant Self-Attention, in Pytorch.
SE3 Transformer - Pytorch Implementation of SE3-Transformers for Equivariant Self-Attention, in Pytorch. May be needed for replicating Alphafold2 resu
Pytorch Implementation of Various Point Transformers
Pytorch Implementation of Various Point Transformers Recently, various methods applied transformers to point clouds: PCT: Point Cloud Transformer (Men
KoBART model on huggingface transformers
KoBART-Transformers SKT에서 공개한 KoBART를 편리하게 사용할 수 있게 transformers로 포팅하였습니다. Install (Optional) BartModel과 PreTrainedTokenizerFast를 이용하면 설치하실 필요 없습니다. p
Framework for fine-tuning pretrained transformers for Named-Entity Recognition (NER) tasks
NERDA Not only is NERDA a mesmerizing muppet-like character. NERDA is also a python package, that offers a slick easy-to-use interface for fine-tuning
SAINT PyTorch implementation
SAINT-pytorch A Simple pyTorch implementation of "Towards an Appropriate Query, Key, and Value Computation for Knowledge Tracing" based on https://arx
Transformers are Graph Neural Networks!
🚀 Gated Graph Transformers Gated Graph Transformers for graph-level property prediction, i.e. graph classification and regression. Associated article
Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learning algorithms
Coach Coach is a python reinforcement learning framework containing implementation of many state-of-the-art algorithms. It exposes a set of easy-to-us
Visualizer for neural network, deep learning, and machine learning models
Netron is a viewer for neural network, deep learning and machine learning models. Netron supports ONNX (.onnx, .pb, .pbtxt), Keras (.h5, .keras), Tens