1317 Repositories
Python sequence-to-sequence-models Libraries
A collection of various deep learning architectures, models, and tips
Deep Learning Models A collection of various deep learning architectures, models, and tips for TensorFlow and PyTorch in Jupyter Notebooks. Traditiona
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, TensorFlow Lite, Keras, Caffe, Darknet, ncnn,
Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Imagenet
Neural-Backed Decision Trees · Site · Paper · Blog · Video Alvin Wan, *Lisa Dunlap, *Daniel Ho, Jihan Yin, Scott Lee, Henry Jin, Suzanne Petryk, Sarah
Quickly and easily create / train a custom DeepDream model
Dream-Creator This project aims to simplify the process of creating a custom DeepDream model by using pretrained GoogleNet models and custom image dat
Implementation of Neural Distance Embeddings for Biological Sequences (NeuroSEED) in PyTorch
Neural Distance Embeddings for Biological Sequences Official implementation of Neural Distance Embeddings for Biological Sequences (NeuroSEED) in PyTo
WRENCH: Weak supeRvision bENCHmark
🔧 What is it? Wrench is a benchmark platform containing diverse weak supervision tasks. It also provides a common and easy framework for development
Lingvo is a framework for building neural networks in Tensorflow, particularly sequence models.
Lingvo is a framework for building neural networks in Tensorflow, particularly sequence models.
A Tools that help Data Scientists and ML engineers train and deploy ML models.
Domino Research This repo contains projects under active development by the Domino R&D team. We build tools that help Data Scientists and ML engineers
fastgradio is a python library to quickly build and share gradio interfaces of your trained fastai models.
fastgradio is a python library to quickly build and share gradio interfaces of your trained fastai models.
GluonMM is a library of transformer models for computer vision and multi-modality research
GluonMM is a library of transformer models for computer vision and multi-modality research. It contains reference implementations of widely adopted baseline models and also research work from Amazon Research.
BMInf (Big Model Inference) is a low-resource inference package for large-scale pretrained language models (PLMs).
BMInf (Big Model Inference) is a low-resource inference package for large-scale pretrained language models (PLMs).
Code for ACL'2021 paper WARP 🌀 Word-level Adversarial ReProgramming
Code for ACL'2021 paper WARP 🌀 Word-level Adversarial ReProgramming. Outperforming `GPT-3` on SuperGLUE Few-Shot text classification.
TruthfulQA: Measuring How Models Imitate Human Falsehoods
TruthfulQA: Measuring How Models Imitate Human Falsehoods
Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context Code in both PyTorch and TensorFlow
Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context This repository contains the code in both PyTorch and TensorFlow for our paper
🤗 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
[ICLR'19] Trellis Networks for Sequence Modeling
TrellisNet for Sequence Modeling This repository contains the experiments done in paper Trellis Networks for Sequence Modeling by Shaojie Bai, J. Zico
Pervasive Attention: 2D Convolutional Networks for Sequence-to-Sequence Prediction
This is a fork of Fairseq(-py) with implementations of the following models: Pervasive Attention - 2D Convolutional Neural Networks for Sequence-to-Se
A Fast Sequence Transducer Implementation with PyTorch Bindings
transducer A Fast Sequence Transducer Implementation with PyTorch Bindings. The corresponding publication is Sequence Transduction with Recurrent Neur
PyTorch implementation of convolutional neural networks-based text-to-speech synthesis models
Deepvoice3_pytorch PyTorch implementation of convolutional networks-based text-to-speech synthesis models: arXiv:1710.07654: Deep Voice 3: Scaling Tex
Sequence modeling benchmarks and temporal convolutional networks
Sequence Modeling Benchmarks and Temporal Convolutional Networks (TCN) This repository contains the experiments done in the work An Empirical Evaluati
StarGAN - Official PyTorch Implementation (CVPR 2018)
StarGAN - Official PyTorch Implementation ***** New: StarGAN v2 is available at https://github.com/clovaai/stargan-v2 ***** This repository provides t
The PASS dataset: pretrained models and how to get the data - PASS: Pictures without humAns for Self-Supervised Pretraining
The PASS dataset: pretrained models and how to get the data - PASS: Pictures without humAns for Self-Supervised Pretraining
Silero Models: pre-trained speech-to-text, text-to-speech models and benchmarks made embarrassingly simple
Silero Models: pre-trained speech-to-text, text-to-speech models and benchmarks made embarrassingly simple
Discretized Integrated Gradients for Explaining Language Models (EMNLP 2021)
Discretized Integrated Gradients for Explaining Language Models (EMNLP 2021) Overview of paths used in DIG and IG. w is the word being attributed. The
The GitHub repository for the paper: “Time Series is a Special Sequence: Forecasting with Sample Convolution and Interaction“.
SCINet This is the original PyTorch implementation of the following work: Time Series is a Special Sequence: Forecasting with Sample Convolution and I
Tevatron is a simple and efficient toolkit for training and running dense retrievers with deep language models.
Tevatron Tevatron is a simple and efficient toolkit for training and running dense retrievers with deep language models. The toolkit has a modularized
In this repository we have tested 3 VQA models on the ImageCLEF-2019 dataset.
Med-VQA In this repository we have tested 3 VQA models on the ImageCLEF-2019 dataset. Two of these are made on top of Facebook AI Reasearch's Multi-Mo
Sequence-to-Sequence learning using PyTorch
Seq2Seq in PyTorch This is a complete suite for training sequence-to-sequence models in PyTorch. It consists of several models and code to both train
Implementation of Squeezenet in pytorch, pretrained models on Cifar 10 data to come
Pytorch Squeeznet Pytorch implementation of Squeezenet model as described in https://arxiv.org/abs/1602.07360 on cifar-10 Data. The definition of Sque
Reinforcement learning models in ViZDoom environment
DoomNet DoomNet is a ViZDoom agent trained by reinforcement learning. The agent is a neural network that outputs a probability of actions given only p
Sequence to Sequence Models with PyTorch
Sequence to Sequence models with PyTorch This repository contains implementations of Sequence to Sequence (Seq2Seq) models in PyTorch At present it ha
PICARD - Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Models
This is the official implementation of the following paper: Torsten Scholak, Nathan Schucher, Dzmitry Bahdanau. PICARD - Parsing Incrementally for Con
Hierarchical unsupervised and semi-supervised topic models for sparse count data with CorEx
Anchored CorEx: Hierarchical Topic Modeling with Minimal Domain Knowledge Correlation Explanation (CorEx) is a topic model that yields rich topics tha
Neural network models for joint POS tagging and dependency parsing (CoNLL 2017-2018)
Neural Network Models for Joint POS Tagging and Dependency Parsing Implementations of joint models for POS tagging and dependency parsing, as describe
Model Agnostic Confidence Estimator (MACEST) - A Python library for calibrating Machine Learning models' confidence scores
Model Agnostic Confidence Estimator (MACEST) - A Python library for calibrating Machine Learning models' confidence scores
Official pytorch implementation of "Scaling-up Disentanglement for Image Translation", ICCV 2021.
Official pytorch implementation of "Scaling-up Disentanglement for Image Translation", ICCV 2021.
Code and dataset for the EMNLP 2021 Finding paper "Can NLI Models Verify QA Systems’ Predictions?"
Code and dataset for the EMNLP 2021 Finding paper "Can NLI Models Verify QA Systems’ Predictions?"
A2T: Towards Improving Adversarial Training of NLP Models (EMNLP 2021 Findings)
A2T: Towards Improving Adversarial Training of NLP Models This is the source code for the EMNLP 2021 (Findings) paper "Towards Improving Adversarial T
EMNLP'2021: Can Language Models be Biomedical Knowledge Bases?
BioLAMA BioLAMA is biomedical factual knowledge triples for probing biomedical LMs. The triples are collected and pre-processed from three sources: CT
Supervised Contrastive Learning for Downstream Optimized Sequence Representations
SupCL-Seq 📖 Supervised Contrastive Learning for Downstream Optimized Sequence representations (SupCS-Seq) accepted to be published in EMNLP 2021, ext
Code for evaluating Japanese pretrained models provided by NTT Ltd.
japanese-dialog-transformers 日本語の説明文はこちら This repository provides the information necessary to evaluate the Japanese Transformer Encoder-decoder dialo
TorchGeo is a PyTorch domain library, similar to torchvision, that provides datasets, transforms, samplers, and pre-trained models specific to geospatial data.
TorchGeo is a PyTorch domain library, similar to torchvision, that provides datasets, transforms, samplers, and pre-trained models specific to geospatial data.
The repository for the paper: Multilingual Translation via Grafting Pre-trained Language Models
Graformer The repository for the paper: Multilingual Translation via Grafting Pre-trained Language Models Graformer (also named BridgeTransformer in t
A Django application that provides country choices for use with forms, flag icons static files, and a country field for models.
Django Countries A Django application that provides country choices for use with forms, flag icons static files, and a country field for models. Insta
A BitField extension for Django Models
django-bitfield Provides a BitField like class (using a BigIntegerField) for your Django models. (If you're upgrading from a version before 1.2 the AP
This is a vision-based 3d model manipulation and control UI
Manipulation of 3D Models Using Hand Gesture This program allows user to manipulation 3D models (.obj format) with their hands. The project support bo
A collection of SOTA Image Classification Models in PyTorch
A collection of SOTA Image Classification Models in PyTorch
[EMNLP 2021] LM-Critic: Language Models for Unsupervised Grammatical Error Correction
LM-Critic: Language Models for Unsupervised Grammatical Error Correction This repo provides the source code & data of our paper: LM-Critic: Language M
Code & Models for 3DETR - an End-to-end transformer model for 3D object detection
3DETR: An End-to-End Transformer Model for 3D Object Detection PyTorch implementation and models for 3DETR. 3DETR (3D DEtection TRansformer) is a simp
Object Moderation Layer
django-oml Welcome to the documentation for django-oml! OML means Object Moderation Layer, the idea is to have a mixin model that allows you to modera
CPT: A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and Generation
CPT This repository contains code and checkpoints for CPT. CPT: A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and Gener
Must-read papers on improving efficiency for pre-trained language models.
Must-read papers on improving efficiency for pre-trained language models.
Keras attention models including botnet,CoaT,CoAtNet,CMT,cotnet,halonet,resnest,resnext,resnetd,volo,mlp-mixer,resmlp,gmlp,levit
Keras_cv_attention_models Keras_cv_attention_models Usage Basic Usage Layers Model surgery AotNet ResNetD ResNeXt ResNetQ BotNet VOLO ResNeSt HaloNet
ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models (ICCV 2021 Oral)
ILVR + ADM This is the implementation of ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models (ICCV 2021 Oral). This repository is h
Selene is a Python library and command line interface for training deep neural networks from biological sequence data such as genomes.
Selene is a Python library and command line interface for training deep neural networks from biological sequence data such as genomes.
Code for the paper: Sequence-to-Sequence Learning with Latent Neural Grammars
Code for the paper: Sequence-to-Sequence Learning with Latent Neural Grammars
Codebase for Diffusion Models Beat GANS on Image Synthesis.
Codebase for Diffusion Models Beat GANS on Image Synthesis.
Demonstrates how to divide a DL model into multiple IR model files (division) and introduce a simplest way to implement a custom layer works with OpenVINO IR models.
Demonstration of OpenVINO techniques - Model-division and a simplest-way to support custom layers Description: Model Optimizer in Intel(r) OpenVINO(tm
This repository contains the official release of the model "BanglaBERT" and associated downstream finetuning code and datasets introduced in the paper titled "BanglaBERT: Combating Embedding Barrier in Multilingual Models for Low-Resource Language Understanding".
BanglaBERT This repository contains the official release of the model "BanglaBERT" and associated downstream finetuning code and datasets introduced i
Fourier-Bayesian estimation of stochastic volatility models
fourier-bayesian-sv-estimation Fourier-Bayesian estimation of stochastic volatility models Code used to run the numerical examples of "Bayesian Approa
Code and checkpoints for training the transformer-based Table QA models introduced in the paper TAPAS: Weakly Supervised Table Parsing via Pre-training.
End-to-end neural table-text understanding models.
This repository accompanies our paper “Do Prompt-Based Models Really Understand the Meaning of Their Prompts?”
This repository accompanies our paper “Do Prompt-Based Models Really Understand the Meaning of Their Prompts?” Usage To replicate our results in Secti
Code for the paper "Reinforcement Learning as One Big Sequence Modeling Problem"
Trajectory Transformer Code release for Reinforcement Learning as One Big Sequence Modeling Problem. Installation All python dependencies are in envir
PyTorch implementation of "Representing Shape Collections with Alignment-Aware Linear Models" paper.
deep-linear-shapes PyTorch implementation of "Representing Shape Collections with Alignment-Aware Linear Models" paper. If you find this code useful i
FLAML is a lightweight Python library that finds accurate machine learning models automatically, efficiently and economically
FLAML - Fast and Lightweight AutoML
MWPToolkit is a PyTorch-based toolkit for Math Word Problem (MWP) solving.
MWPToolkit is a PyTorch-based toolkit for Math Word Problem (MWP) solving. It is a comprehensive framework for research purpose that integrates popular MWP benchmark datasets and typical deep learning-based MWP algorithms.
The code repository for EMNLP 2021 paper "Vision Guided Generative Pre-trained Language Models for Multimodal Abstractive Summarization".
Vision Guided Generative Pre-trained Language Models for Multimodal Abstractive Summarization [Paper] accepted at the EMNLP 2021: Vision Guided Genera
This repo uses a combination of logits and feature distillation method to teach the PSPNet model of ResNet18 backbone with the PSPNet model of ResNet50 backbone. All the models are trained and tested on the PASCAL-VOC2012 dataset.
PSPNet-logits and feature-distillation Introduction This repository is based on PSPNet and modified from semseg and Pixelwise_Knowledge_Distillation_P
Ptorch NLU, a Chinese text classification and sequence annotation toolkit, supports multi class and multi label classification tasks of Chinese long text and short text, and supports sequence annotation tasks such as Chinese named entity recognition, part of speech tagging and word segmentation.
Pytorch-NLU,一个中文文本分类、序列标注工具包,支持中文长文本、短文本的多类、多标签分类任务,支持中文命名实体识别、词性标注、分词等序列标注任务。 Ptorch NLU, a Chinese text classification and sequence annotation toolkit, supports multi class and multi label classification tasks of Chinese long text and short text, and supports sequence annotation tasks such as Chinese named entity recognition, part of speech tagging and word segmentation.
This repository contains various models targetting multimodal representation learning, multimodal fusion for downstream tasks such as multimodal sentiment analysis.
Multimodal Deep Learning 🎆 🎆 🎆 Announcing the multimodal deep learning repository that contains implementation of various deep learning-based model
DeepConsensus uses gap-aware sequence transformers to correct errors in Pacific Biosciences (PacBio) Circular Consensus Sequencing (CCS) data.
DeepConsensus DeepConsensus uses gap-aware sequence transformers to correct errors in Pacific Biosciences (PacBio) Circular Consensus Sequencing (CCS)
Ranking Models in Unlabeled New Environments (iccv21)
Ranking Models in Unlabeled New Environments Prerequisites This code uses the following libraries Python 3.7 NumPy PyTorch 1.7.0 + torchivision 0.8.1
pyntcloud is a Python library for working with 3D point clouds.
pyntcloud is a Python library for working with 3D point clouds.
Official implementation of particle-based models (GNS and DPI-Net) on the Physion dataset.
Physion: Evaluating Physical Prediction from Vision in Humans and Machines [paper] Daniel M. Bear, Elias Wang, Damian Mrowca, Felix J. Binder, Hsiao-Y
PaddleViT: State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 2.0+
PaddlePaddle Vision Transformers State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 🤖 PaddlePaddle Visual Transformers (PaddleViT or
The official repository for our paper "The Devil is in the Detail: Simple Tricks Improve Systematic Generalization of Transformers". We significantly improve the systematic generalization of transformer models on a variety of datasets using simple tricks and careful considerations.
Codebase for training transformers on systematic generalization datasets. The official repository for our EMNLP 2021 paper The Devil is in the Detail:
Codes to pre-train Japanese T5 models
t5-japanese Codes to pre-train a T5 (Text-to-Text Transfer Transformer) model pre-trained on Japanese web texts. The model is available at https://hug
EMNLP 2021 Adapting Language Models for Zero-shot Learning by Meta-tuning on Dataset and Prompt Collections
Adapting Language Models for Zero-shot Learning by Meta-tuning on Dataset and Prompt Collections Ruiqi Zhong, Kristy Lee*, Zheng Zhang*, Dan Klein EMN
Ongoing research training transformer language models at scale, including: BERT & GPT-2
Megatron (1 and 2) is a large, powerful transformer developed by the Applied Deep Learning Research team at NVIDIA.
Official implementation of the MM'21 paper Constrained Graphic Layout Generation via Latent Optimization
[MM'21] Constrained Graphic Layout Generation via Latent Optimization This repository provides the official code for the paper "Constrained Graphic La
Code for our ALiBi method for transformer language models.
Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation This repository contains the code and models for our paper Tra
Source Code For Template-Based Named Entity Recognition Using BART
Template-Based NER Source Code For Template-Based Named Entity Recognition Using BART Training Training train.py Inference inference.py Corpus ATIS (h
A comprehensive CRUD API generator for SQLALchemy.
FastAPI Quick CRUD Introduction Advantage Constraint Getting started Installation Usage Design Path Parameter Query Parameter Request Body Upsert Intr
Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet)
This is a playground for pytorch beginners, which contains predefined models on popular dataset. Currently we support mnist, svhn cifar10, cifar100 st
Re-implementation of the Noise Contrastive Estimation algorithm for pyTorch, following "Noise-contrastive estimation: A new estimation principle for unnormalized statistical models." (Gutmann and Hyvarinen, AISTATS 2010)
Noise Contrastive Estimation for pyTorch Overview This repository contains a re-implementation of the Noise Contrastive Estimation algorithm, implemen
Sequence-to-Sequence learning using PyTorch
Seq2Seq in PyTorch This is a complete suite for training sequence-to-sequence models in PyTorch. It consists of several models and code to both train
Collection of generative models in Pytorch version.
pytorch-generative-model-collections Original : [Tensorflow version] Pytorch implementation of various GANs. This repository was re-implemented with r
Implementation of Token Shift GPT - An autoregressive model that solely relies on shifting the sequence space for mixing
Token Shift GPT Implementation of Token Shift GPT - An autoregressive model that relies solely on shifting along the sequence dimension and feedforwar
Running Google MoveNet Multipose Tracking models on OpenVINO.
MoveNet MultiPose Tracking on OpenVINO
Music Source Separation; Train & Eval & Inference piplines and pretrained models we used for 2021 ISMIR MDX Challenge.
Music Source Separation with Channel-wise Subband Phase Aware ResUnet (CWS-PResUNet) Introduction This repo contains the pretrained Music Source Separ
Deep learning models for change detection of remote sensing images
Change Detection Models (Remote Sensing) Python library with Neural Networks for Change Detection based on PyTorch. ⚡ ⚡ ⚡ I am trying to build this pr
This repository contains the code and models for the following paper.
DC-ShadowNet Introduction This is an implementation of the following paper DC-ShadowNet: Single-Image Hard and Soft Shadow Removal Using Unsupervised
We present a framework for training multi-modal deep learning models on unlabelled video data by forcing the network to learn invariances to transformations applied to both the audio and video streams.
Multi-Modal Self-Supervision using GDT and StiCa This is an official pytorch implementation of papers: Multi-modal Self-Supervision from Generalized D
Learning Generative Models of Textured 3D Meshes from Real-World Images, ICCV 2021
Learning Generative Models of Textured 3D Meshes from Real-World Images This is the reference implementation of "Learning Generative Models of Texture
Generative Models as a Data Source for Multiview Representation Learning
GenRep Project Page | Paper Generative Models as a Data Source for Multiview Representation Learning Ali Jahanian, Xavier Puig, Yonglong Tian, Phillip
Empower Sequence Labeling with Task-Aware Language Model
LM-LSTM-CRF Check Our New NER Toolkit 🚀 🚀 🚀 Inference: LightNER: inference w. models pre-trained / trained w. any following tools, efficiently. Tra
Evaluation suite for large-scale language models.
This repo contains code for running the evaluations and reproducing the results from the Jurassic-1 Technical Paper (see blog post), with current support for running the tasks through both the AI21 Studio API and OpenAI's GPT3 API.
IMS-Toucan is a toolkit to train state-of-the-art Speech Synthesis models
IMS-Toucan is a toolkit to train state-of-the-art Speech Synthesis models. Everything is pure Python and PyTorch based to keep it as simple and beginner-friendly, yet powerful as possible.
yolox_backbone is a deep-learning library and is a collection of YOLOX Backbone models.
YOLOX-Backbone yolox-backbone is a deep-learning library and is a collection of YOLOX backbone models. Install pip install yolox-backbone Load a Pret