Python Point-Transformers Resources

BiPointNet: Binary Neural Network for Point Clouds Created by Haotong Qin, Zhongang Cai, Mingyuan Zhang, Yifu Ding, Haiyu Zhao, Shuai Yi, Xianglong Li

universal-computation Overview Official codebase for Pretrained Transformers as Universal Computation Engines. Contains demo notebook and scripts to r

UP-DETR: Unsupervised Pre-training for Object Detection with Transformers This is the official PyTorch implementation and models for UP-DETR paper: @a

XPandas (extended Pandas) implements 1D and 2D data containers for storing type-heterogeneous tabular data of any type, and encapsulates feature extra

Operating system Build Status Linux/Mac Windows tick tick is a Python 3 module for statistical learning, with a particular emphasis on time-dependent

COCO LM Pretraining (wip) Implementation of COCO-LM, Correcting and Contrasting Text Sequences for Language Model Pretraining, in Pytorch. They were a

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. Hudson* & C. Lawrence Zitnick *I wish to thank Christopher D. Manning for the fruitf

Transformer in Transformer Implementation of Transformer in Transformer, pixel level attention paired with patch level attention for image c

Medical-Transformer Pytorch Code for the paper "Medical Transformer: Gated Axial-Attention for Medical Image Segmentation" About this repo: This repo

Ivy vision focuses predominantly on 3D vision, with functions for camera geometry, image projections, co-ordinate frame transformations, forward warping, inverse warping, optical flow, depth triangulation, voxel grids, point clouds, signed distance functions, and others. Check out the docs for more info!

UnsupervisedR&R: Unsupervised Pointcloud Registration via Differentiable Rendering This repository holds all the code and data for our recent work on

SETR - Pytorch Since the original paper (Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers.) has no official

TransUNet This repo holds code for TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation Usage

TimeSformer - Pytorch Implementation of TimeSformer, a pure and simple attention-based solution for reaching SOTA on video classification.

BurpParamFlagger A Burp extension adding a passive scan check to flag parameters whose name or value may indicate a possible insertion point for SSRF

Self-attention building blocks for computer vision applications in PyTorch Implementation of self attention mechanisms for computer vision in PyTorch

Det3D is the first 3D Object Detection toolbox which provides off the box implementations of many 3D object detection algorithms such as PointPillars, SECOND, PIXOR, etc, as well as state-of-the-art methods on major benchmarks like KITTI(ViP) and nuScenes(CBGS).

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

Camphr - spaCy plugin for Transformers, Udify, Elmo, etc. Camphr is a Natural Language Processing library that helps in seamless integration for a wid

A Deep Learning NLP/NLU library by Intel® AI Lab Overview | Models | Installation | Examples | Documentation | Tutorials | Contributing NLP Architect

Fast-Bert New - Learning Rate Finder for Text Classification Training (borrowed with thanks from https://github.com/davidtvs/pytorch-lr-finder) Suppor

spacy-transformers: Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy This package provides spaCy components and architectures to use tr

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

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 Jina is a deep learning-powered search framework for building cross-/multi-modal search systems (e.g

Sentence Transformers: Multilingual Sentence Embeddings using BERT / RoBERTa / XLM-RoBERTa & Co. with PyTorch This framework provides an easy method t

Provides an implementation of today's most used tokenizers, with a focus on performance and versatility. Main features: Train new vocabularies and tok

State-of-the-art Natural Language Processing for PyTorch and TensorFlow 2.0 🤗 Transformers provides thousands of pretrained models to perform tasks o

[Preprint] "TransGAN: Two Transformers Can Make One Strong GAN", Yifan Jiang, Shiyu Chang, Zhangyang Wang

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

Camphr - spaCy plugin for Transformers, Udify, Elmo, etc. Camphr is a Natural Language Processing library that helps in seamless integration for a wid

A Deep Learning NLP/NLU library by Intel® AI Lab Overview | Models | Installation | Examples | Documentation | Tutorials | Contributing NLP Architect

Fast-Bert New - Learning Rate Finder for Text Classification Training (borrowed with thanks from https://github.com/davidtvs/pytorch-lr-finder) Suppor

spacy-transformers: Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy This package provides spaCy components and architectures to use tr

Haystack is an end-to-end framework for Question Answering & Neural search that enables you to ... ... ask questions in natural language and find gran

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 Jina is a deep learning-powered search framework for building cross-/multi-modal search systems (e.g

Sentence Transformers: Multilingual Sentence Embeddings using BERT / RoBERTa / XLM-RoBERTa & Co. with PyTorch This framework provides an easy method t

Provides an implementation of today's most used tokenizers, with a focus on performance and versatility. Main features: Train new vocabularies and tok

State-of-the-art Natural Language Processing for PyTorch and TensorFlow 2.0 🤗 Transformers provides thousands of pretrained models to perform tasks o

This project is no longer maintained March 2020 Update: Please go see the amazing Pysa tutorial that should get you up to speed finding security vulne

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 This repository contains PyTorch evaluation code, training code and pretrained models for DeiT (Data-Efficient

Bottleneck Transformer - Pytorch Implementation of Bottleneck Transformer, SotA visual recognition model with convolution + attention that outperforms

PCT: Point Cloud Transformer This is a Jittor implementation of PCT: Point Cloud Transformer.

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

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

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

Point Transformer - Pytorch Implementation of the Point Transformer self-attention layer, in Pytorch. The simple circuit above seemed to have allowed

Graph Transformer Architecture Source code for the paper "A Generalization of Transformer Networks to Graphs" by Vijay Prakash Dwivedi and Xavier Bres

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.

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 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) This repository implements methods for explainability in Vision Transformers

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 Recently, various methods applied transformers to point clouds: PCT: Point Cloud Transformer (Men

PCT: Point Cloud Transformer This is a Pytorch implementation of PCT: Point Cloud Transformer.

KoBART-Transformers SKT에서 공개한 KoBART를 편리하게 사용할 수 있게 transformers로 포팅하였습니다. Install (Optional) BartModel과 PreTrainedTokenizerFast를 이용하면 설치하실 필요 없습니다. p

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 A Simple pyTorch implementation of "Towards an Appropriate Query, Key, and Value Computation for Knowledge Tracing" based on https://arx

🚀 Gated Graph Transformers Gated Graph Transformers for graph-level property prediction, i.e. graph classification and regression. Associated article

Bayesian Methods for Hackers Using Python and PyMC The Bayesian method is the natural approach to inference, yet it is hidden from readers behind chap