712 Repositories
Python transformers-bert Libraries
This demo showcase the use of onnxruntime-rs with a GPU on CUDA 11 to run Bert in a data pipeline with Rust.
Demo BERT ONNX pipeline written in rust This demo showcase the use of onnxruntime-rs with a GPU on CUDA 11 to run Bert in a data pipeline with Rust. R
This project is a sample demo of Arxiv search related to AI/ML Papers built using Streamlit, sentence-transformers and Faiss.
This project is a sample demo of Arxiv search related to AI/ML Papers built using Streamlit, sentence-transformers and Faiss.
Active learning for text classification in Python
Active Learning allows you to efficiently label training data in a small-data scenario.
Implementation of Multistream Transformers in Pytorch
Multistream Transformers Implementation of Multistream Transformers in Pytorch. This repository deviates slightly from the paper, where instead of usi
[ICCV'21] PlaneTR: Structure-Guided Transformers for 3D Plane Recovery
PlaneTR: Structure-Guided Transformers for 3D Plane Recovery This is the official implementation of our ICCV 2021 paper News There maybe some bugs in
Implementing SimCSE(paper, official repository) using TensorFlow 2 and KR-BERT.
KR-BERT-SimCSE Implementing SimCSE(paper, official repository) using TensorFlow 2 and KR-BERT. Training Unsupervised python train_unsupervised.py --mi
REST API for sentence tokenization and embedding using Multilingual Universal Sentence Encoder.
MUSE stands for Multilingual Universal Sentence Encoder - multilingual extension (supports 16 languages) of Universal Sentence Encoder (USE).
Learned Token Pruning for Transformers
LTP: Learned Token Pruning for Transformers Check our paper for more details. Installation We follow the same installation procedure as the original H
Relative Positional Encoding for Transformers with Linear Complexity
Stochastic Positional Encoding (SPE) This is the source code repository for the ICML 2021 paper Relative Positional Encoding for Transformers with Lin
A PyTorch implementation of ViTGAN based on paper ViTGAN: Training GANs with Vision Transformers.
ViTGAN: Training GANs with Vision Transformers A PyTorch implementation of ViTGAN based on paper ViTGAN: Training GANs with Vision Transformers. Refer
🤗 Transformers: State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX.
English | 简体中文 | 繁體中文 State-of-the-art Natural Language Processing for Jax, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrained mo
RoBERTa Marathi Language model trained from scratch during huggingface 🤗 x flax community week
RoBERTa base model for Marathi Language (मराठी भाषा) Pretrained model on Marathi language using a masked language modeling (MLM) objective. RoBERTa wa
Official source for spanish Language Models and resources made @ BSC-TEMU within the "Plan de las Tecnologías del Lenguaje" (Plan-TL).
Spanish Language Models 💃🏻 Corpora 📃 Corpora Number of documents Size (GB) BNE 201,080,084 570GB Models 🤖 RoBERTa-base BNE: https://huggingface.co
A heterogeneous entity-augmented academic language model based on Open Academic Graph (OAG)
Library | Paper | Slack We released two versions of OAG-BERT in CogDL package. OAG-BERT is a heterogeneous entity-augmented academic language model wh
EsViT: Efficient self-supervised Vision Transformers
Efficient Self-Supervised Vision Transformers (EsViT) PyTorch implementation for EsViT, built with two techniques: A multi-stage Transformer architect
Pytorch code for ICRA'21 paper: "Hierarchical Cross-Modal Agent for Robotics Vision-and-Language Navigation"
Hierarchical Cross-Modal Agent for Robotics Vision-and-Language Navigation This repository is the pytorch implementation of our paper: Hierarchical Cr
Official repository for the paper, MidiBERT-Piano: Large-scale Pre-training for Symbolic Music Understanding.
MidiBERT-Piano Authors: Yi-Hui (Sophia) Chou, I-Chun (Bronwin) Chen Introduction This is the official repository for the paper, MidiBERT-Piano: Large-
Empirical Study of Transformers for Source Code & A Simple Approach for Handling Out-of-Vocabulary Identifiers in Deep Learning for Source Code
Transformers for variable misuse, function naming and code completion tasks The official PyTorch implementation of: Empirical Study of Transformers fo
VD-BERT: A Unified Vision and Dialog Transformer with BERT
VD-BERT: A Unified Vision and Dialog Transformer with BERT PyTorch Code for the following paper at EMNLP2020: Title: VD-BERT: A Unified Vision and Dia
General Multi-label Image Classification with Transformers
General Multi-label Image Classification with Transformers Jack Lanchantin, Tianlu Wang, Vicente Ordóñez Román, Yanjun Qi Conference on Computer Visio
[Preprint] "Chasing Sparsity in Vision Transformers: An End-to-End Exploration" by Tianlong Chen, Yu Cheng, Zhe Gan, Lu Yuan, Lei Zhang, Zhangyang Wang
Chasing Sparsity in Vision Transformers: An End-to-End Exploration Codes for [Preprint] Chasing Sparsity in Vision Transformers: An End-to-End Explora
VD-BERT: A Unified Vision and Dialog Transformer with BERT
VD-BERT: A Unified Vision and Dialog Transformer with BERT PyTorch Code for the following paper at EMNLP2020: Title: VD-BERT: A Unified Vision and Dia
Official repository for the paper "Going Beyond Linear Transformers with Recurrent Fast Weight Programmers"
Recurrent Fast Weight Programmers This is the official repository containing the code we used to produce the experimental results reported in the pape
Huggingface Transformers + Adapters = ❤️
adapter-transformers A friendly fork of HuggingFace's Transformers, adding Adapters to PyTorch language models adapter-transformers is an extension of
Flexible interface for high-performance research using SOTA Transformers leveraging Pytorch Lightning, Transformers, and Hydra.
Flexible interface for high performance research using SOTA Transformers leveraging Pytorch Lightning, Transformers, and Hydra. What is Lightning Tran
The source codes for ACL 2021 paper 'BoB: BERT Over BERT for Training Persona-based Dialogue Models from Limited Personalized Data'
BoB: BERT Over BERT for Training Persona-based Dialogue Models from Limited Personalized Data This repository provides the implementation details for
PyTorch impelementations of BERT-based Spelling Error Correction Models
PyTorch impelementations of BERT-based Spelling Error Correction Models
PyTorch impelementations of BERT-based Spelling Error Correction Models.
PyTorch impelementations of BERT-based Spelling Error Correction Models. 基于BERT的文本纠错模型,使用PyTorch实现。
A BERT-based reverse-dictionary of Korean proverbs
Wisdomify A BERT-based reverse-dictionary of Korean proverbs. 김유빈 : 모델링 / 데이터 수집 / 프로젝트 설계 / back-end 김종윤 : 데이터 수집 / 프로젝트 설계 / front-end Quick Start C
AllenNLP integration for Shiba: Japanese CANINE model
Allennlp Integration for Shiba allennlp-shiab-model is a Python library that provides AllenNLP integration for shiba-model. SHIBA is an approximate re
LoFTR:Detector-Free Local Feature Matching with Transformers CVPR 2021
LoFTR-with-train-script LoFTR:Detector-Free Local Feature Matching with Transformers CVPR 2021 (with train script --- unofficial ---). About Megadepth
This is an official implementation for "Video Swin Transformers".
Video Swin Transformer By Ze Liu*, Jia Ning*, Yue Cao, Yixuan Wei, Zheng Zhang, Stephen Lin and Han Hu. This repo is the official implementation of "V
LV-BERT: Exploiting Layer Variety for BERT (Findings of ACL 2021)
LV-BERT Introduction In this repo, we introduce LV-BERT by exploiting layer variety for BERT. For detailed description and experimental results, pleas
LETR: Line Segment Detection Using Transformers without Edges
LETR: Line Segment Detection Using Transformers without Edges Introduction This repository contains the official code and pretrained models for Line S
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
LV-BERT: Exploiting Layer Variety for BERT (Findings of ACL 2021)
LV-BERT Introduction In this repo, we introduce LV-BERT by exploiting layer variety for BERT. For detailed description and experimental results, pleas
TunBERT is the first release of a pre-trained BERT model for the Tunisian dialect using a Tunisian Common-Crawl-based dataset.
TunBERT is the first release of a pre-trained BERT model for the Tunisian dialect using a Tunisian Common-Crawl-based dataset. TunBERT was applied to three NLP downstream tasks: Sentiment Analysis (SA), Tunisian Dialect Identification (TDI) and Reading Comprehension Question-Answering (RCQA)
PyTorch evaluation code for Delving Deep into the Generalization of Vision Transformers under Distribution Shifts.
Out-of-distribution Generalization Investigation on Vision Transformers This repository contains PyTorch evaluation code for Delving Deep into the Gen
Python Implementation of ``Modeling the Influence of Verb Aspect on the Activation of Typical Event Locations with BERT'' (Findings of ACL: ACL 2021)
BERT-for-Surprisal Python Implementation of ``Modeling the Influence of Verb Aspect on the Activation of Typical Event Locations with BERT'' (Findings
easySpeech is an open-source Python wrapper for google speech to text API that doesn't require PyAudio(So you especially windows user don't have to deal with the errors while installing PyAudio) and also works with hugging face transformers
easySpeech easySpeech is an open source python wrapper for google speech to text api that doesn't require PyAaudio(So you specially windows user don't
An interpreter for RASP as described in the ICML 2021 paper "Thinking Like Transformers"
RASP Setup Mac or Linux Run ./setup.sh . It will create a python3 virtual environment and install the dependencies for RASP. It will also try to insta
2021海华AI挑战赛·中文阅读理解·技术组·第三名
文字是人类用以记录和表达的最基本工具,也是信息传播的重要媒介。透过文字与符号,我们可以追寻人类文明的起源,可以传播知识与经验,读懂文字是认识与了解的第一步。对于人工智能而言,它的核心问题之一就是认知,而认知的核心则是语义理解。
Official implementation of "SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers"
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers Figure 1: Performance of SegFormer-B0 to SegFormer-B5. Project page
This is the official implementation for "Do Transformers Really Perform Bad for Graph Representation?".
Graphormer By Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng*, Guolin Ke, Di He*, Yanming Shen and Tie-Yan Liu. This repo is the official impl
Baseline code for Korean open domain question answering(ODQA)
Open-Domain Question Answering(ODQA)는 다양한 주제에 대한 문서 집합으로부터 자연어 질의에 대한 답변을 찾아오는 task입니다. 이때 사용자 질의에 답변하기 위해 주어지는 지문이 따로 존재하지 않습니다. 따라서 사전에 구축되어있는 Knowl
Code + pre-trained models for the paper Keeping Your Eye on the Ball Trajectory Attention in Video Transformers
Motionformer This is an official pytorch implementation of paper Keeping Your Eye on the Ball: Trajectory Attention in Video Transformers. In this rep
Load What You Need: Smaller Multilingual Transformers for Pytorch and TensorFlow 2.0.
Smaller Multilingual Transformers This repository shares smaller versions of multilingual transformers that keep the same representations offered by t
Official repository for "On Improving Adversarial Transferability of Vision Transformers" (2021)
Improving-Adversarial-Transferability-of-Vision-Transformers Muzammal Naseer, Kanchana Ranasinghe, Salman Khan, Fahad Khan, Fatih Porikli arxiv link A
Official PyTorch implementation of Less is More: Pay Less Attention in Vision Transformers.
Less is More: Pay Less Attention in Vision Transformers Official PyTorch implementation of Less is More: Pay Less Attention in Vision Transformers. By
CATs: Semantic Correspondence with Transformers
CATs: Semantic Correspondence with Transformers For more information, check out the paper on [arXiv]. Training with different backbones and evaluation
Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning
We challenge a common assumption underlying most supervised deep learning: that a model makes a prediction depending only on its parameters and the features of a single input. To this end, we introduce a general-purpose deep learning architecture that takes as input the entire dataset instead of processing one datapoint at a time.
The official implementation of You Only Compress Once: Towards Effective and Elastic BERT Compression via Exploit-Explore Stochastic Nature Gradient.
You Only Compress Once: Towards Effective and Elastic BERT Compression via Exploit-Explore Stochastic Nature Gradient (paper) @misc{zhang2021compress,
DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification
DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification Created by Yongming Rao, Wenliang Zhao, Benlin Liu, Jiwen Lu, Jie Zhou, Ch
Source code for NAACL 2021 paper "TR-BERT: Dynamic Token Reduction for Accelerating BERT Inference"
TR-BERT Source code and dataset for "TR-BERT: Dynamic Token Reduction for Accelerating BERT Inference". The code is based on huggaface's transformers.
Official repository for "Intriguing Properties of Vision Transformers" (2021)
Intriguing Properties of Vision Transformers Muzammal Naseer, Kanchana Ranasinghe, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, & Ming-Hsuan Yang P
Official repository for HOTR: End-to-End Human-Object Interaction Detection with Transformers (CVPR'21, Oral Presentation)
Official PyTorch Implementation for HOTR: End-to-End Human-Object Interaction Detection with Transformers (CVPR'2021, Oral Presentation) HOTR: End-to-
This is an official implementation of CvT: Introducing Convolutions to Vision Transformers.
Introduction This is an official implementation of CvT: Introducing Convolutions to Vision Transformers. We present a new architecture, named Convolut
Chinese clinical named entity recognition using pre-trained BERT model
Chinese clinical named entity recognition (CNER) using pre-trained BERT model Introduction Code for paper Chinese clinical named entity recognition wi
simpleT5 is built on top of PyTorch-lightning⚡️ and Transformers🤗 that lets you quickly train your T5 models.
Quickly train T5 models in just 3 lines of code + ONNX support simpleT5 is built on top of PyTorch-lightning ⚡️ and Transformers 🤗 that lets you quic
Implementation of CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification
CrossViT : Cross-Attention Multi-Scale Vision Transformer for Image Classification This is an unofficial PyTorch implementation of CrossViT: Cross-Att
Code for the ACL2021 paper "Lexicon Enhanced Chinese Sequence Labelling Using BERT Adapter"
Lexicon Enhanced Chinese Sequence Labeling Using BERT Adapter Code and checkpoints for the ACL2021 paper "Lexicon Enhanced Chinese Sequence Labelling
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
This is an official implementation of CvT: Introducing Convolutions to Vision Transformers.
Introduction This is an official implementation of CvT: Introducing Convolutions to Vision Transformers. We present a new architecture, named Convolut
Research code for CVPR 2021 paper "End-to-End Human Pose and Mesh Reconstruction with Transformers"
MeshTransformer ✨ This is our research code of End-to-End Human Pose and Mesh Reconstruction with Transformers. MEsh TRansfOrmer is a simple yet effec
Medical Image Segmentation using Squeeze-and-Expansion Transformers
Medical Image Segmentation using Squeeze-and-Expansion Transformers Introduction This repository contains the code of the IJCAI'2021 paper 'Medical Im
(CVPR2021) Kaleido-BERT: Vision-Language Pre-training on Fashion Domain
Kaleido-BERT: Vision-Language Pre-training on Fashion Domain Mingchen Zhuge*, Dehong Gao*, Deng-Ping Fan#, Linbo Jin, Ben Chen, Haoming Zhou, Minghui
Pytorch code for ICRA'21 paper: "Hierarchical Cross-Modal Agent for Robotics Vision-and-Language Navigation"
Hierarchical Cross-Modal Agent for Robotics Vision-and-Language Navigation This repository is the pytorch implementation of our paper: Hierarchical Cr
Contains code for the paper "Vision Transformers are Robust Learners".
Vision Transformers are Robust Learners This repository contains the code for the paper Vision Transformers are Robust Learners by Sayak Paul* and Pin
Train 🤗transformers with DeepSpeed: ZeRO-2, ZeRO-3
Fork from https://github.com/huggingface/transformers/tree/86d5fb0b360e68de46d40265e7c707fe68c8015b/examples/pytorch/language-modeling at 2021.05.17.
XtremeDistil framework for distilling/compressing massive multilingual neural network models to tiny and efficient models for AI at scale
XtremeDistilTransformers for Distilling Massive Multilingual Neural Networks ACL 2020 Microsoft Research [Paper] [Video] Releasing [XtremeDistilTransf
Implementation of gMLP, an all-MLP replacement for Transformers, in Pytorch
Implementation of gMLP, an all-MLP replacement for Transformers, in Pytorch
This repository contains PyTorch code for Robust Vision Transformers.
This repository contains PyTorch code for Robust Vision Transformers.
[NAACL & ACL 2021] SapBERT: Self-alignment pretraining for BERT.
SapBERT: Self-alignment pretraining for BERT This repo holds code for the SapBERT model presented in our NAACL 2021 paper: Self-Alignment Pretraining
MILES is a multilingual text simplifier inspired by LSBert - A BERT-based lexical simplification approach proposed in 2018. Unlike LSBert, MILES uses the bert-base-multilingual-uncased model, as well as simple language-agnostic approaches to complex word identification (CWI) and candidate ranking.
MILES Multilingual Lexical Simplifier Explore the docs » Read LSBert Paper · Report Bug · Request Feature About The Project MILES is a multilingual te
TrackFormer: Multi-Object Tracking with Transformers
TrackFormer: Multi-Object Tracking with Transformers This repository provides the official implementation of the TrackFormer: Multi-Object Tracking wi
Exploring whether attention is necessary for vision transformers
Do You Even Need Attention? A Stack of Feed-Forward Layers Does Surprisingly Well on ImageNet Paper/Report TL;DR We replace the attention layer in a v
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
Integrating the Best of TF into PyTorch, for Machine Learning, Natural Language Processing, and Text Generation. This is part of the CASL project: http://casl-project.ai/
Texar-PyTorch is a toolkit aiming to support a broad set of machine learning, especially natural language processing and text generation tasks. Texar
Pytorch-Named-Entity-Recognition-with-BERT
BERT NER Use google BERT to do CoNLL-2003 NER ! Train model using Python and Inference using C++ ALBERT-TF2.0 BERT-NER-TENSORFLOW-2.0 BERT-SQuAD Requi
Google AI 2018 BERT pytorch implementation
BERT-pytorch Pytorch implementation of Google AI's 2018 BERT, with simple annotation BERT 2018 BERT: Pre-training of Deep Bidirectional Transformers f
jiant is an NLP toolkit
jiant is an NLP toolkit The multitask and transfer learning toolkit for natural language processing research Why should I use jiant? jiant supports mu
keras implement of transformers for humans
keras implement of transformers for humans
An easier way to build neural search on the cloud
Jina is geared towards building search systems for any kind of data, including text, images, audio, video and many more. With the modular design & multi-layer abstraction, you can leverage the efficient patterns to build the system by parts, or chaining them into a Flow for an end-to-end experience.
Codes for our paper "SentiLARE: Sentiment-Aware Language Representation Learning with Linguistic Knowledge" (EMNLP 2020)
SentiLARE: Sentiment-Aware Language Representation Learning with Linguistic Knowledge Introduction SentiLARE is a sentiment-aware pre-trained language
ISTR: End-to-End Instance Segmentation with Transformers (https://arxiv.org/abs/2105.00637)
This is the project page for the paper: ISTR: End-to-End Instance Segmentation via Transformers, Jie Hu, Liujuan Cao, Yao Lu, ShengChuan Zhang, Yan Wa
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
An Easy-to-use, Modular and Prolongable package of deep-learning based Named Entity Recognition Models.
DeepNER An Easy-to-use, Modular and Prolongable package of deep-learning based Named Entity Recognition Models. This repository contains complex Deep
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
LightSeq: A High-Performance Inference Library for Sequence Processing and Generation
LightSeq is a high performance inference library for sequence processing and generation implemented in CUDA. It enables highly efficient computation of modern NLP models such as BERT, GPT2, Transformer, etc. It is therefore best useful for Machine Translation, Text Generation, Dialog, Language Modelling, and other related tasks using these models.
PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO
Self-Supervised Vision Transformers with DINO PyTorch implementation and pretrained models for DINO. For details, see Emerging Properties in Self-Supe
Geometry-Free View Synthesis: Transformers and no 3D Priors
Geometry-Free View Synthesis: Transformers and no 3D Priors Geometry-Free View Synthesis: Transformers and no 3D Priors Robin Rombach*, Patrick Esser*
Twins: Revisiting the Design of Spatial Attention in Vision Transformers
Twins: Revisiting the Design of Spatial Attention in Vision Transformers Very recently, a variety of vision transformer architectures for dense predic
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
Code for the paper "Improving Vision-and-Language Navigation with Image-Text Pairs from the Web" (ECCV 2020)
Improving Vision-and-Language Navigation with Image-Text Pairs from the Web Arjun Majumdar, Ayush Shrivastava, Stefan Lee, Peter Anderson, Devi Parikh
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
Pytorch version of BERT-whitening
BERT-whitening This is the Pytorch implementation of "Whitening Sentence Representations for Better Semantics and Faster Retrieval". BERT-whitening is