600 Repositories
Python onnx-transformers Libraries
Train and use generative text models in a few lines of code.
blather Train and use generative text models in a few lines of code. To see blather in action check out the colab notebook! Installation Use the packa
PyTorch implementation of Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets
Simple PyTorch Implementation of "Grokking" Implementation of Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets Usage Running
Convert ONNX model graph to Keras model format.
Convert ONNX model graph to Keras model format.
Official PyTorch implementation for paper "Efficient Two-Stage Detection of Human–Object Interactions with a Novel Unary–Pairwise Transformer"
UPT: Unary–Pairwise Transformers This repository contains the official PyTorch implementation for the paper Frederic Z. Zhang, Dylan Campbell and Step
Implementation of NÜWA, state of the art attention network for text to video synthesis, in Pytorch
NÜWA - Pytorch (wip) Implementation of NÜWA, state of the art attention network for text to video synthesis, in Pytorch. This repository will be popul
Mastering Transformers, published by Packt
Mastering Transformers This is the code repository for Mastering Transformers, published by Packt. Build state-of-the-art models from scratch with adv
Panoptic SegFormer: Delving Deeper into Panoptic Segmentation with Transformers
Panoptic SegFormer: Delving Deeper into Panoptic Segmentation with Transformers Results results on COCO val Backbone Method Lr Schd PQ Config Download
なりすまし検出(anti-spoof-mn3)のWebカメラ向けデモ
FaceDetection-Anti-Spoof-Demo なりすまし検出(anti-spoof-mn3)のWebカメラ向けデモです。 モデルはPINTO_model_zoo/191_anti-spoof-mn3からONNX形式のモデルを使用しています。 Requirement mediapipe
Revisiting Pre-trained Models for Chinese Natural Language Processing (Findings of EMNLP 2020)
This repository contains the resources in our paper "Revisiting Pre-trained Models for Chinese Natural Language Processing", which will be published i
Code for ACL 2019 Paper: "COMET: Commonsense Transformers for Automatic Knowledge Graph Construction"
To run a generation experiment (either conceptnet or atomic), follow these instructions: First Steps First clone, the repo: git clone https://github.c
Code for the ACL 2021 paper "Structural Guidance for Transformer Language Models"
Structural Guidance for Transformer Language Models This repository accompanies the paper, Structural Guidance for Transformer Language Models, publis
PyTorch code for EMNLP 2019 paper "LXMERT: Learning Cross-Modality Encoder Representations from Transformers".
LXMERT: Learning Cross-Modality Encoder Representations from Transformers Our servers break again :(. I have updated the links so that they should wor
Research code for ECCV 2020 paper "UNITER: UNiversal Image-TExt Representation Learning"
UNITER: UNiversal Image-TExt Representation Learning This is the official repository of UNITER (ECCV 2020). This repository currently supports finetun
Code for Editing Factual Knowledge in Language Models
KnowledgeEditor Code for Editing Factual Knowledge in Language Models (https://arxiv.org/abs/2104.08164). @inproceedings{decao2021editing, title={Ed
OOD Generalization and Detection (ACL 2020)
Pretrained Transformers Improve Out-of-Distribution Robustness How does pretraining affect out-of-distribution robustness? We create an OOD benchmark
EMNLP 2021 paper The Devil is in the Detail: Simple Tricks Improve Systematic Generalization of Transformers.
Codebase for training transformers on systematic generalization datasets. The official repository for our EMNLP 2021 paper The Devil is in the Detail:
Understanding the Difficulty of Training Transformers
Admin Understanding the Difficulty of Training Transformers Guided by our analyses, we propose Adaptive Model Initialization (Admin), which successful
Optimizing Deeper Transformers on Small Datasets
DT-Fixup Optimizing Deeper Transformers on Small Datasets Paper published in ACL 2021: arXiv Detailed instructions to replicate our results in the pap
Official Pytorch Implementation of Length-Adaptive Transformer (ACL 2021)
Length-Adaptive Transformer This is the official Pytorch implementation of Length-Adaptive Transformer. For detailed information about the method, ple
Research code for "What to Pre-Train on? Efficient Intermediate Task Selection", EMNLP 2021
efficient-task-transfer This repository contains code for the experiments in our paper "What to Pre-Train on? Efficient Intermediate Task Selection".
PyTorch implementation of the ACL, 2021 paper Parameter-efficient Multi-task Fine-tuning for Transformers via Shared Hypernetworks.
Parameter-efficient Multi-task Fine-tuning for Transformers via Shared Hypernetworks This repo contains the PyTorch implementation of the ACL, 2021 pa
This repository contains the implementation of the paper: Federated Distillation of Natural Language Understanding with Confident Sinkhorns
Federated Distillation of Natural Language Understanding with Confident Sinkhorns This repository provides an alternative method for ensembled distill
Code for "ATISS: Autoregressive Transformers for Indoor Scene Synthesis", NeurIPS 2021
ATISS: Autoregressive Transformers for Indoor Scene Synthesis This repository contains the code that accompanies our paper ATISS: Autoregressive Trans
End-to-End Referring Video Object Segmentation with Multimodal Transformers
End-to-End Referring Video Object Segmentation with Multimodal Transformers This repo contains the official implementation of the paper: End-to-End Re
Pre-Training 3D Point Cloud Transformers with Masked Point Modeling
Point-BERT: Pre-Training 3D Point Cloud Transformers with Masked Point Modeling Created by Xumin Yu*, Lulu Tang*, Yongming Rao*, Tiejun Huang, Jie Zho
Code for our ICCV 2021 Paper "OadTR: Online Action Detection with Transformers".
Code for our ICCV 2021 Paper "OadTR: Online Action Detection with Transformers".
Official Pytorch Code for the paper TransWeather
TransWeather Official Code for the paper TransWeather, Arxiv Tech Report 2021 Paper | Website About this repo: This repo hosts the implentation code,
Haystack is an open source NLP framework that leverages Transformer models.
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
Simple and Distributed Machine Learning
Synapse Machine Learning SynapseML (previously MMLSpark) is an open source library to simplify the creation of scalable machine learning pipelines. Sy
KakaoBrain KoGPT (Korean Generative Pre-trained Transformer)
KoGPT KoGPT (Korean Generative Pre-trained Transformer) https://github.com/kakaobrain/kogpt https://huggingface.co/kakaobrain/kogpt Model Descriptions
Conversational text Analysis using various NLP techniques
PyConverse Let me try first Installation pip install pyconverse Usage Please try this notebook that demos the core functionalities: basic usage noteb
Python scripts for performing stereo depth estimation using the MobileStereoNet model in ONNX
ONNX-MobileStereoNet Python scripts for performing stereo depth estimation using the MobileStereoNet model in ONNX Stereo depth estimation on the cone
Package to compute Mauve, a similarity score between neural text and human text. Install with `pip install mauve-text`.
MAUVE MAUVE is a library built on PyTorch and HuggingFace Transformers to measure the gap between neural text and human text with the eponymous MAUVE
Make differentially private training of transformers easy for everyone
private-transformers This codebase facilitates fast experimentation of differentially private training of Hugging Face transformers. What is this? Why
PeCo: Perceptual Codebook for BERT Pre-training of Vision Transformers
PeCo: Perceptual Codebook for BERT Pre-training of Vision Transformers
Spectralformer: Rethinking hyperspectral image classification with transformers
Spectralformer: Rethinking hyperspectral image classification with transformers Danfeng Hong, Zhu Han, Jing Yao, Lianru Gao, Bing Zhang, Antonio Plaza
Automated question generation and question answering from Turkish texts using text-to-text transformers
Turkish Question Generation Offical source code for "Automated question generation & question answering from Turkish texts using text-to-text transfor
Tandem Mass Spectrum Prediction with Graph Transformers
MassFormer This is the original implementation of MassFormer, a graph transformer for small molecule MS/MS prediction. Check out the preprint on arxiv
Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized Codes
Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized C
CLIPImageClassifier wraps clip image model from transformers
CLIPImageClassifier CLIPImageClassifier wraps clip image model from transformers. CLIPImageClassifier is initialized with the argument classes, these
An easy to use Natural Language Processing library and framework for predicting, training, fine-tuning, and serving up state-of-the-art NLP models.
Welcome to AdaptNLP A high level framework and library for running, training, and deploying state-of-the-art Natural Language Processing (NLP) models
Use fastai-v2 with HuggingFace's pretrained transformers
FastHugs Use fastai v2 with HuggingFace's pretrained transformers, see the notebooks below depending on your task: Text classification: fasthugs_seq_c
A library that integrates huggingface transformers with the world of fastai, giving fastai devs everything they need to train, evaluate, and deploy transformer specific models.
blurr A library that integrates huggingface transformers with version 2 of the fastai framework Install You can now pip install blurr via pip install
This is the official PyTorch implementation for "Mesa: A Memory-saving Training Framework for Transformers".
A Memory-saving Training Framework for Transformers This is the official PyTorch implementation for Mesa: A Memory-saving Training Framework for Trans
Feature-engine is a Python library with multiple transformers to engineer and select features for use in machine learning models.
Feature-engine is a Python library with multiple transformers to engineer and select features for use in machine learning models. Feature-engine's transformers follow scikit-learn's functionality with fit() and transform() methods to first learn the transforming parameters from data and then transform the data.
Multi-modal Vision Transformers Excel at Class-agnostic Object Detection
Multi-modal Vision Transformers Excel at Class-agnostic Object Detection
This is the official PyTorch implementation for "Mesa: A Memory-saving Training Framework for Transformers".
Mesa: A Memory-saving Training Framework for Transformers This is the official PyTorch implementation for Mesa: A Memory-saving Training Framework for
Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models.
Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models. Solve a variety of tasks with pre-trained models or finetune them in
[BMVC'21] Official PyTorch Implementation of Grounded Situation Recognition with Transformers
Grounded Situation Recognition with Transformers Paper | Model Checkpoint This is the official PyTorch implementation of Grounded Situation Recognitio
Multiple types of NN model optimization environments. It is possible to directly access the host PC GUI and the camera to verify the operation. Intel iHD GPU (iGPU) support. NVIDIA GPU (dGPU) support.
mtomo Multiple types of NN model optimization environments. It is possible to directly access the host PC GUI and the camera to verify the operation.
DeepHawkeye is a library to detect unusual patterns in images using features from pretrained neural networks
English | 简体中文 Introduction DeepHawkeye is a library to detect unusual patterns in images using features from pretrained neural networks Reference Pat
Python scripts for performing lane detection using the LSTR model in ONNX
ONNX LSTR Lane Detection Python scripts for performing lane detection using the Lane Shape Prediction with Transformers (LSTR) model in ONNX. Requirem
This repository includes the official project for the paper: TransMix: Attend to Mix for Vision Transformers.
TransMix: Attend to Mix for Vision Transformers This repository includes the official project for the paper: TransMix: Attend to Mix for Vision Transf
ByteTrack(Multi-Object Tracking by Associating Every Detection Box)のPythonでのONNX推論サンプル
ByteTrack-ONNX-Sample ByteTrack(Multi-Object Tracking by Associating Every Detection Box)のPythonでのONNX推論サンプルです。 ONNXに変換したモデルも同梱しています。 変換自体を試したい方はByteT
This repository includes the official project for the paper: TransMix: Attend to Mix for Vision Transformers.
TransMix: Attend to Mix for Vision Transformers This repository includes the official project for the paper: TransMix: Attend to Mix for Vision Transf
[BMVC'21] Official PyTorch Implementation of Grounded Situation Recognition with Transformers
Grounded Situation Recognition with Transformers Paper | Model Checkpoint This is the official PyTorch implementation of Grounded Situation Recognitio
Official source for spanish Language Models and resources made @ BSC-TEMU within the "Plan de las Tecnologías del Lenguaje" (Plan-TL).
Spanish Language Models 💃🏻 A repository part of the MarIA project. Corpora 📃 Corpora Number of documents Number of tokens Size (GB) BNE 201,080,084
🛠️ Tools for Transformers compression using Lightning ⚡
Bert-squeeze is a repository aiming to provide code to reduce the size of Transformer-based models or decrease their latency at inference time.
PESTO: Switching Point based Dynamic and Relative Positional Encoding for Code-Mixed Languages
PESTO: Switching Point based Dynamic and Relative Positional Encoding for Code-Mixed Languages Abstract NLP applications for code-mixed (CM) or mix-li
AOT (Associating Objects with Transformers) in PyTorch
An efficient modular implementation of Associating Objects with Transformers for Video Object Segmentation in PyTorch
Spectralformer: Rethinking hyperspectral image classification with transformers
The code in this toolbox implements the "Spectralformer: Rethinking hyperspectral image classification with transformers". More specifically, it is detailed as follow.
Implementation of Uniformer, a simple attention and 3d convolutional net that achieved SOTA in a number of video classification tasks
Uniformer - Pytorch Implementation of Uniformer, a simple attention and 3d convolutional net that achieved SOTA in a number of video classification ta
WHENet - ONNX, OpenVINO, TFLite, TensorRT, EdgeTPU, CoreML, TFJS, YOLOv4/YOLOv4-tiny-3L
HeadPoseEstimation-WHENet-yolov4-onnx-openvino ONNX, OpenVINO, TFLite, TensorRT, EdgeTPU, CoreML, TFJS, YOLOv4/YOLOv4-tiny-3L 1. Usage $ git clone htt
Transformers and related deep network architectures are summarized and implemented here.
Transformers: from NLP to CV This is a practical introduction to Transformers from Natural Language Processing (NLP) to Computer Vision (CV) Introduct
Boundary-aware Transformers for Skin Lesion Segmentation
Boundary-aware Transformers for Skin Lesion Segmentation Introduction This is an official release of the paper Boundary-aware Transformers for Skin Le
KakaoBrain KoGPT (Korean Generative Pre-trained Transformer)
KoGPT KoGPT (Korean Generative Pre-trained Transformer) https://github.com/kakaobrain/kogpt https://huggingface.co/kakaobrain/kogpt Model Descriptions
ML for NLP and Computer Vision.
Sparrow is our open-source ML product. It runs on Skipper MLOps infrastructure.
Partially offline multi-language translator built upon Huggingface transformers.
Translate Command-line interface to translation pipelines, powered by Huggingface transformers. This tool can download translation models, and then us
Implementation of H-Transformer-1D, Hierarchical Attention for Sequence Learning using 🤗 transformers
hierarchical-transformer-1d Implementation of H-Transformer-1D, Hierarchical Attention for Sequence Learning using 🤗 transformers In Progress!! 2021.
Tandem Mass Spectrum Prediction with Graph Transformers
MassFormer This is the original implementation of MassFormer, a graph transformer for small molecule MS/MS prediction. Check out the preprint on arxiv
AI-UPV at IberLEF-2021 DETOXIS task: Toxicity Detection in Immigration-Related Web News Comments Using Transformers and Statistical Models
AI-UPV at IberLEF-2021 DETOXIS task: Toxicity Detection in Immigration-Related Web News Comments Using Transformers and Statistical Models Description
Certified Patch Robustness via Smoothed Vision Transformers
Certified Patch Robustness via Smoothed Vision Transformers This repository contains the code for replicating the results of our paper: Certified Patc
Implementation of Hourglass Transformer, in Pytorch, from Google and OpenAI
Hourglass Transformer - Pytorch (wip) Implementation of Hourglass Transformer, in Pytorch. It will also contain some of my own ideas about how to make
🦅 Pretrained BigBird Model for Korean (up to 4096 tokens)
Pretrained BigBird Model for Korean What is BigBird • How to Use • Pretraining • Evaluation Result • Docs • Citation 한국어 | English What is BigBird? Bi
ICCV2021, Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet
Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet, ICCV 2021 Update: 2021/03/11: update our new results. Now our T2T-ViT-14 w
Efficient Training of Audio Transformers with Patchout
PaSST: Efficient Training of Audio Transformers with Patchout This is the implementation for Efficient Training of Audio Transformers with Patchout Pa
Taming Transformers for High-Resolution Image Synthesis
Taming Transformers for High-Resolution Image Synthesis CVPR 2021 (Oral) Taming Transformers for High-Resolution Image Synthesis Patrick Esser*, Robin
Security evaluation module with onnx, pytorch, and SecML.
🚀 🐼 🔥 PandaVision Integrate and automate security evaluations with onnx, pytorch, and SecML! Installation Starting the server without Docker If you
Transformers Wav2Vec2 + Parlance's CTCDecodeTransformers Wav2Vec2 + Parlance's CTCDecode
🤗 Transformers Wav2Vec2 + Parlance's CTCDecode Introduction This repo shows how 🤗 Transformers can be used in combination with Parlance's ctcdecode
Tools for Optuna, MLflow and the integration of both.
HPOflow - Sphinx DOC Tools for Optuna, MLflow and the integration of both. Detailed documentation with examples can be found here: Sphinx DOC Table of
A collection of Scikit-Learn compatible time series transformers and tools.
tsfeast A collection of Scikit-Learn compatible time series transformers and tools. Installation Create a virtual environment and install: From PyPi p
A python library for highly configurable transformers - easing model architecture search and experimentation.
A python library for highly configurable transformers - easing model architecture search and experimentation.
Pytorch library for fast transformer implementations
Transformers are very successful models that achieve state of the art performance in many natural language tasks
x-transformers-paddle 2.x version
x-transformers-paddle x-transformers-paddle 2.x version paddle 2.x版本 https://github.com/lucidrains/x-transformers 。 requirements paddlepaddle-gpu==2.2
PECOS - Prediction for Enormous and Correlated Spaces
PECOS - Predictions for Enormous and Correlated Output Spaces PECOS is a versatile and modular machine learning (ML) framework for fast learning and i
This codebase facilitates fast experimentation of differentially private training of Hugging Face transformers.
private-transformers This codebase facilitates fast experimentation of differentially private training of Hugging Face transformers. What is this? Why
Monocular 3D pose estimation. OpenVINO. CPU inference or iGPU (OpenCL) inference.
human-pose-estimation-3d-python-cpp RealSenseD435 (RGB) 480x640 + CPU Corei9 45 FPS (Depth is not used) 1. Run 1-1. RealSenseD435 (RGB) 480x640 + CPU
Japanese Long-Unit-Word Tokenizer with RemBertTokenizerFast of Transformers
Japanese-LUW-Tokenizer Japanese Long-Unit-Word (国語研長単位) Tokenizer for Transformers based on 青空文庫 Basic Usage from transformers import RemBertToken
(to be released) [NeurIPS'21] Transformers Generalize DeepSets and Can be Extended to Graphs and Hypergraphs
Higher-Order Transformers Kim J, Oh S, Hong S, Transformers Generalize DeepSets and Can be Extended to Graphs and Hypergraphs, NeurIPS 2021. [arxiv] W
Repository for the paper titled: "When is BERT Multilingual? Isolating Crucial Ingredients for Cross-lingual Transfer"
When is BERT Multilingual? Isolating Crucial Ingredients for Cross-lingual Transfer This repository contains code for our paper titled "When is BERT M
Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting
Autoformer (NeurIPS 2021) Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting Time series forecasting is a c
Transformers implementation for Fall 2021 Clinic
Installation Download miniconda3 if not already installed You can check by running typing conda in command prompt. Use conda to create an environment
PSGAN running with ncnn⚡妆容迁移/仿妆⚡Imitation Makeup/Makeup Transfer⚡
PSGAN running with ncnn⚡妆容迁移/仿妆⚡Imitation Makeup/Makeup Transfer⚡
SpeechBrain is an open-source and all-in-one speech toolkit based on PyTorch.
The SpeechBrain Toolkit SpeechBrain is an open-source and all-in-one speech toolkit based on PyTorch. The goal is to create a single, flexible, and us
jel - Japanese Entity Linker - is Bi-encoder based entity linker for japanese.
jel: Japanese Entity Linker jel - Japanese Entity Linker - is Bi-encoder based entity linker for japanese. Usage Currently, link and question methods
A method for cleaning and classifying text using transformers.
NLP Translation and Classification The repository contains a method for classifying and cleaning text using NLP transformers. Overview The input data
🤗 Transformers: State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX.
English | 简体中文 | 繁體中文 | 한국어 State-of-the-art Natural Language Processing for Jax, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrai
This repository is the code of the paper "Sparse Spatial Transformers for Few-Shot Learning".
🌟 Sparse Spatial Transformers for Few-Shot Learning This code implements the Sparse Spatial Transformers for Few-Shot Learning(SSFormers). Our code i
Multivariate Time Series Forecasting with efficient Transformers. Code for the paper "Long-Range Transformers for Dynamic Spatiotemporal Forecasting."
Spacetimeformer Multivariate Forecasting This repository contains the code for the paper, "Long-Range Transformers for Dynamic Spatiotemporal Forecast
A little Python application to auto tag your photos with the power of machine learning.
Tag Machine A little Python application to auto tag your photos with the power of machine learning. Report a bug or request a feature Table of Content