162 Repositories
Python pretrained Libraries
[ACL 2022] LinkBERT: A Knowledgeable Language Model 😎 Pretrained with Document Links
LinkBERT: A Knowledgeable Language Model Pretrained with Document Links This repo provides the model, code & data of our paper: LinkBERT: Pretraining
HugsVision is a easy to use huggingface wrapper for state-of-the-art computer vision
HugsVision is an open-source and easy to use all-in-one huggingface wrapper for computer vision. The goal is to create a fast, flexible and user-frien
Self-Supervised Vision Transformers Learn Visual Concepts in Histopathology (LMRL Workshop, NeurIPS 2021)
Self-Supervised Vision Transformers Learn Visual Concepts in Histopathology Self-Supervised Vision Transformers Learn Visual Concepts in Histopatholog
SciFive: a text-text transformer model for biomedical literature
SciFive SciFive provided a Text-Text framework for biomedical language and natural language in NLP. Under the T5's framework and desrbibed in the pape
[ICLR 2022] Pretraining Text Encoders with Adversarial Mixture of Training Signal Generators
AMOS This repository contains the scripts for fine-tuning AMOS pretrained models on GLUE and SQuAD 2.0 benchmarks. Paper: Pretraining Text Encoders wi
Pretrained models for Jax/Haiku; MobileNet, ResNet, VGG, Xception.
Pre-trained image classification models for Jax/Haiku Jax/Haiku Applications are deep learning models that are made available alongside pre-trained we
SIGIR'22 paper: Axiomatically Regularized Pre-training for Ad hoc Search
Introduction This codebase contains source-code of the Python-based implementation (ARES) of our SIGIR 2022 paper. Chen, Jia, et al. "Axiomatically Re
OpenDelta - An Open-Source Framework for Paramter Efficient Tuning.
OpenDelta is a toolkit for parameter efficient methods (we dub it as delta tuning), by which users could flexibly assign (or add) a small amount parameters to update while keeping the most paramters frozen. By using OpenDelta, users could easily implement prefix-tuning, adapters, Lora, or any other types of delta tuning with preferred PTMs.
Topic Discovery via Latent Space Clustering of Pretrained Language Model Representations
TopClus The source code used for Topic Discovery via Latent Space Clustering of Pretrained Language Model Representations, published in WWW 2022. Requ
Datasets and pretrained Models for StyleGAN3 ...
Datasets and pretrained Models for StyleGAN3 ... Dear arfiticial friend, this is a collection of artistic datasets and models that we have put togethe
Pretrained Japanese BERT models
Pretrained Japanese BERT models This is a repository of pretrained Japanese BERT models. The models are available in Transformers by Hugging Face. Mod
The source code for Generating Training Data with Language Models: Towards Zero-Shot Language Understanding.
SuperGen The source code for Generating Training Data with Language Models: Towards Zero-Shot Language Understanding. Requirements Before running, you
Transformers provides thousands of pretrained models to perform tasks on different modalities such as text, vision, and audio.
English | 简体中文 | 繁體中文 | 한국어 State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrained models
A collection of pre-trained StyleGAN2 models trained on different datasets at different resolution.
Awesome Pretrained StyleGAN2 A collection of pre-trained StyleGAN2 models trained on different datasets at different resolution. Note the readme is a
BaseCls BaseCls 是一个基于 MegEngine 的预训练模型库,帮助大家挑选或训练出更适合自己科研或者业务的模型结构
BaseCls BaseCls 是一个基于 MegEngine 的预训练模型库,帮助大家挑选或训练出更适合自己科研或者业务的模型结构。 文档地址:https://basecls.readthedocs.io 安装 安装环境 BaseCls 需要 Python = 3.6。 BaseCls 依赖 M
Using pretrained GROVER to extract the atomic fingerprints from molecule
Extracting atomic fingerprints from molecules using pretrained Graph Neural Network models (GROVER).
Main Results on ImageNet with Pretrained Models
This repository contains Pytorch evaluation code, training code and pretrained models for the following projects: SPACH (A Battle of Network Structure
f-BRS: Rethinking Backpropagating Refinement for Interactive Segmentation
f-BRS: Rethinking Backpropagating Refinement for Interactive Segmentation [Paper] [PyTorch] [MXNet] [Video] This repository provides code for training
T‘rex Park is a Youzan sponsored project. Offering Chinese NLP and image models pretrained from E-commerce datasets
T‘rex Park is a Youzan sponsored project. Offering Chinese NLP and image models pretrained from E-commerce datasets (product titles, images, comments, etc.).
Generic Foreground Segmentation in Images
Pixel Objectness The following repository contains pretrained model for pixel objectness. Please visit our project page for the paper and visual resul
A minimal yet resourceful implementation of diffusion models (along with pretrained models + synthetic images for nine datasets)
A minimal yet resourceful implementation of diffusion models (along with pretrained models + synthetic images for nine datasets)
Natural Language Processing Best Practices & Examples
NLP Best Practices In recent years, natural language processing (NLP) has seen quick growth in quality and usability, and this has helped to drive bus
Adds timm pretrained backbone to pytorch's FasterRcnn model
timmFasterRcnn model_config.py - it returns the model,feat_sizes,output channel and the feat layer names, which is reqd by the Add_FPN.py file Add_FP
CV backbones including GhostNet, TinyNet and TNT, developed by Huawei Noah's Ark Lab.
CV Backbones including GhostNet, TinyNet, TNT (Transformer in Transformer) developed by Huawei Noah's Ark Lab. GhostNet Code TinyNet Code TNT Code Pyr
SOTA easy to use PyTorch-based DL training library
Easily train or fine-tune SOTA computer vision models from one training repository. SuperGradients Introduction Welcome to SuperGradients, a free open
Fast, DB Backed pretrained word embeddings for natural language processing.
Embeddings Embeddings is a python package that provides pretrained word embeddings for natural language processing and machine learning. Instead of lo
Tensorflow Implementation for "Pre-trained Deep Convolution Neural Network Model With Attention for Speech Emotion Recognition"
Tensorflow Implementation for "Pre-trained Deep Convolution Neural Network Model With Attention for Speech Emotion Recognition" Pre-trained Deep Convo
BARTpho: Pre-trained Sequence-to-Sequence Models for Vietnamese
Table of contents Introduction Using BARTpho with fairseq Using BARTpho with transformers Notes BARTpho: Pre-trained Sequence-to-Sequence Models for V
Ensembling Off-the-shelf Models for GAN Training
Vision-aided GAN video (3m) | website | paper Can the collective knowledge from a large bank of pretrained vision models be leveraged to improve GAN t
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
Pretrained language model and its related optimization techniques developed by Huawei Noah's Ark Lab.
Pretrained Language Model This repository provides the latest pretrained language models and its related optimization techniques developed by Huawei N
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
English | 简体中文 | 繁體中文 | 한국어 State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrained models
Awesome Treasure of Transformers Models Collection
💁 Awesome Treasure of Transformers Models for Natural Language processing contains papers, videos, blogs, official repo along with colab Notebooks. 🛫☑️
Experiments on continual learning from a stream of pretrained models.
Ex-model CL Ex-model continual learning is a setting where a stream of experts (i.e. model's parameters) is available and a CL model learns from them
PyTorch implementation of a collections of scalable Video Transformer Benchmarks.
PyTorch implementation of Video Transformer Benchmarks This repository is mainly built upon Pytorch and Pytorch-Lightning. We wish to maintain a colle
Codes and pretrained weights for winning submission of 2021 Brain Tumor Segmentation (BraTS) Challenge
Winning submission to the 2021 Brain Tumor Segmentation Challenge This repo contains the codes and pretrained weights for the winning submission to th
Codes and pretrained weights for winning submission of 2021 Brain Tumor Segmentation (BraTS) Challenge
Winning submission to the 2021 Brain Tumor Segmentation Challenge This repo contains the codes and pretrained weights for the winning submission to th
Music Source Separation; Train & Eval & Inference piplines and pretrained models we used for 2021 ISMIR MDX Challenge.
Introduction 1. Usage (For MSS) 1.1 Prepare running environment 1.2 Use pretrained model 1.3 Train new MSS models from scratch 1.3.1 How to train 1.3.
Pretrained Cost Model for Distributed Constraint Optimization Problems
Pretrained Cost Model for Distributed Constraint Optimization Problems Requirements PyTorch 1.9.0 PyTorch Geometric 1.7.1 Directory structure baseline
[NeurIPS 2021] COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining
COCO-LM This repository contains the scripts for fine-tuning COCO-LM pretrained models on GLUE and SQuAD 2.0 benchmarks. Paper: COCO-LM: Correcting an
A TensorFlow implementation of the Mnemonic Descent Method.
MDM A Tensorflow implementation of the Mnemonic Descent Method. Mnemonic Descent Method: A recurrent process applied for end-to-end face alignment G.
🔪 Elimination based Lightweight Neural Net with Pretrained Weights
ELimNet ELimNet: Eliminating Layers in a Neural Network Pretrained with Large Dataset for Downstream Task Removed top layers from pretrained Efficient
DiffWave is a fast, high-quality neural vocoder and waveform synthesizer.
DiffWave DiffWave is a fast, high-quality neural vocoder and waveform synthesizer. It starts with Gaussian noise and converts it into speech via itera
Optimus: the first large-scale pre-trained VAE language model
Optimus: the first pre-trained Big VAE language model This repository contains source code necessary to reproduce the results presented in the EMNLP 2
[CVPR 2021] VirTex: Learning Visual Representations from Textual Annotations
VirTex: Learning Visual Representations from Textual Annotations Karan Desai and Justin Johnson University of Michigan CVPR 2021 arxiv.org/abs/2006.06
DenseNet Implementation in Keras with ImageNet Pretrained Models
DenseNet-Keras with ImageNet Pretrained Models This is an Keras implementation of DenseNet with ImageNet pretrained weights. The weights are converted
BERTAC (BERT-style transformer-based language model with Adversarially pretrained Convolutional neural network)
BERTAC (BERT-style transformer-based language model with Adversarially pretrained Convolutional neural network) BERTAC is a framework that combines a
Pretrained language model and its related optimization techniques developed by Huawei Noah's Ark Lab.
Pretrained Language Model This repository provides the latest pretrained language models and its related optimization techniques developed by Huawei N
Code associated with the Don't Stop Pretraining ACL 2020 paper
dont-stop-pretraining Code associated with the Don't Stop Pretraining ACL 2020 paper Citation @inproceedings{dontstoppretraining2020, author = {Suchi
PyTorch source code of NAACL 2019 paper "An Embarrassingly Simple Approach for Transfer Learning from Pretrained Language Models"
This repository contains source code for NAACL 2019 paper "An Embarrassingly Simple Approach for Transfer Learning from Pretrained Language Models" (P
Evolutionary Scale Modeling (esm): Pretrained language models for proteins
Evolutionary Scale Modeling This repository contains code and pre-trained weights for Transformer protein language models from Facebook AI Research, i
This repo contains simple to use, pretrained/training-less models for speaker diarization.
PyDiar This repo contains simple to use, pretrained/training-less models for speaker diarization. Supported Models Binary Key Speaker Modeling Based o
An optimized prompt tuning strategy comparable to fine-tuning across model scales and tasks.
P-tuning v2 P-Tuning v2: Prompt Tuning Can Be Comparable to Finetuning Universally Across Scales and Tasks An optimized prompt tuning strategy achievi
Real-time pose estimation accelerated with NVIDIA TensorRT
trt_pose Want to detect hand poses? Check out the new trt_pose_hand project for real-time hand pose and gesture recognition! trt_pose is aimed at enab
TensorFlow port of PyTorch Image Models (timm) - image models with pretrained weights.
TensorFlow-Image-Models Introduction Usage Models Profiling License Introduction TensorfFlow-Image-Models (tfimm) is a collection of image models with
code for EMNLP 2019 paper Text Summarization with Pretrained Encoders
PreSumm This code is for EMNLP 2019 paper Text Summarization with Pretrained Encoders Updates Jan 22 2020: Now you can Summarize Raw Text Input!. Swit
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
This repo contains implementation of different architectures for emotion recognition in conversations.
Emotion Recognition in Conversations Updates 🔥 🔥 🔥 Date Announcements 03/08/2021 🎆 🎆 We have released a new dataset M2H2: A Multimodal Multiparty
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
AfriBERTa: Exploring the Viability of Pretrained Multilingual Language Models for Low-resourced Languages
AfriBERTa: Exploring the Viability of Pretrained Multilingual Language Models for Low-resourced Languages This repository contains the code for the pa
Keras implementation of Deeplab v3+ with pretrained weights
Keras implementation of Deeplabv3+ This repo is not longer maintained. I won't respond to issues but will merge PR DeepLab is a state-of-art deep lear
Segmentation models with pretrained backbones. Keras and TensorFlow Keras.
Python library with Neural Networks for Image Segmentation based on Keras and TensorFlow. The main features of this library are: High level API (just
Modification of convolutional neural net "UNET" for image segmentation in Keras framework
ZF_UNET_224 Pretrained Model Modification of convolutional neural net "UNET" for image segmentation in Keras framework Requirements Python 3.*, Keras
🦅 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
Official code and pretrained models for CTRL-C (Camera calibration TRansformer with Line-Classification).
CTRL-C: Camera calibration TRansformer with Line-Classification This repository contains the official code and pretrained models for CTRL-C (Camera ca
Replication of Pix2Seq with Pretrained Model
Pretrained-Pix2Seq We provide the pre-trained model of Pix2Seq. This version contains new data augmentation. The model is trained for 300 epochs and c
A treasure chest for visual recognition powered by PaddlePaddle
简体中文 | English PaddleClas 简介 飞桨图像识别套件PaddleClas是飞桨为工业界和学术界所准备的一个图像识别任务的工具集,助力使用者训练出更好的视觉模型和应用落地。 近期更新 2021.11.1 发布PP-ShiTu技术报告,新增饮料识别demo 2021.10.23 发
StyleGAN of All Trades: Image Manipulation withOnly Pretrained StyleGAN
StyleGAN of All Trades: Image Manipulation withOnly Pretrained StyleGAN This is the PyTorch implementation of StyleGAN of All Trades: Image Manipulati
PatrickStar enables Larger, Faster, Greener Pretrained Models for NLP. Democratize AI for everyone.
PatrickStar: Parallel Training of Large Language Models via a Chunk-based Memory Management Meeting PatrickStar Pre-Trained Models (PTM) are becoming
PatrickStar enables Larger, Faster, Greener Pretrained Models for NLP. Democratize AI for everyone.
PatrickStar enables Larger, Faster, Greener Pretrained Models for NLP. Democratize AI for everyone.
Team Enigma at ArgMining 2021 Shared Task: Leveraging Pretrained Language Models for Key Point Matching
Team Enigma at ArgMining 2021 Shared Task: Leveraging Pretrained Language Models for Key Point Matching This is our attempt of the shared task on Quan
🤗 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
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
Segmentation models with pretrained backbones. PyTorch.
Python library with Neural Networks for Image Segmentation based on PyTorch. The main features of this library are: High level API (just two lines to
PyTorch and Tensorflow functional model definitions
functional-zoo Model definitions and pretrained weights for PyTorch and Tensorflow PyTorch, unlike lua torch, has autograd in it's core, so using modu
A Word Level Transformer layer based on PyTorch and 🤗 Transformers.
Transformer Embedder A Word Level Transformer layer based on PyTorch and 🤗 Transformers. How to use Install the library from PyPI: pip install transf
LWCC: A LightWeight Crowd Counting library for Python that includes several pretrained state-of-the-art models.
LWCC: A LightWeight Crowd Counting library for Python LWCC is a lightweight crowd counting framework for Python. It wraps four state-of-the-art models
A modular framework for vision & language multimodal research from Facebook AI Research (FAIR)
MMF is a modular framework for vision and language multimodal research from Facebook AI Research. MMF contains reference implementations of state-of-t
[EMNLP 2021] Mirror-BERT: Converting Pretrained Language Models to universal text encoders without labels.
[EMNLP 2021] Mirror-BERT: Converting Pretrained Language Models to universal text encoders without labels.
Finetuner allows one to tune the weights of any deep neural network for better embeddings on search tasks
Finetuner allows one to tune the weights of any deep neural network for better embeddings on search tasks
PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more
PyTorch Image Models Sponsors What's New Introduction Models Features Results Getting Started (Documentation) Train, Validation, Inference Scripts Awe
An NLP library with Awesome pre-trained Transformer models and easy-to-use interface, supporting wide-range of NLP tasks from research to industrial applications.
简体中文 | English News [2021-10-12] PaddleNLP 2.1版本已发布!新增开箱即用的NLP任务能力、Prompt Tuning应用示例与生成任务的高性能推理! 🎉 更多详细升级信息请查看Release Note。 [2021-08-22]《千言:面向事实一致性的生
Mengzi Pretrained Models
中文 | English Mengzi 尽管预训练语言模型在 NLP 的各个领域里得到了广泛的应用,但是其高昂的时间和算力成本依然是一个亟需解决的问题。这要求我们在一定的算力约束下,研发出各项指标更优的模型。 我们的目标不是追求更大的模型规模,而是轻量级但更强大,同时对部署和工业落地更友好的模型。
This repository contains the code for the paper in EMNLP 2021: "HRKD: Hierarchical Relational Knowledge Distillation for Cross-domain Language Model Compression".
HRKD: Hierarchical Relational Knowledge Distillation for Cross-domain Language Model Compression This repository contains the code for the paper in EM
A PyTorch implementation of EfficientNet and EfficientNetV2 (coming soon!)
EfficientNet PyTorch Quickstart Install with pip install efficientnet_pytorch and load a pretrained EfficientNet with: from efficientnet_pytorch impor
A repository that shares tuning results of trained models generated by TensorFlow / Keras. Post-training quantization (Weight Quantization, Integer Quantization, Full Integer Quantization, Float16 Quantization), Quantization-aware training. TensorFlow Lite. OpenVINO. CoreML. TensorFlow.js. TF-TRT. MediaPipe. ONNX. [.tflite,.h5,.pb,saved_model,tfjs,tftrt,mlmodel,.xml/.bin, .onnx]
PINTO_model_zoo Please read the contents of the LICENSE file located directly under each folder before using the model. My model conversion scripts ar
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
Code and data to accompany the camera-ready version of "Cross-Attention is All You Need: Adapting Pretrained Transformers for Machine Translation" in EMNLP 2021
Code and data to accompany the camera-ready version of "Cross-Attention is All You Need: Adapting Pretrained Transformers for Machine Translation" in EMNLP 2021
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.
🤗 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
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
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
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
IndoBERTweet is the first large-scale pretrained model for Indonesian Twitter. Published at EMNLP 2021 (main conference)
IndoBERTweet 🐦 🇮🇩 1. Paper Fajri Koto, Jey Han Lau, and Timothy Baldwin. IndoBERTweet: A Pretrained Language Model for Indonesian Twitter with Effe
Code for the paper in Findings of EMNLP 2021: "EfficientBERT: Progressively Searching Multilayer Perceptron via Warm-up Knowledge Distillation".
This repository contains the code for the paper in Findings of EMNLP 2021: "EfficientBERT: Progressively Searching Multilayer Perceptron via Warm-up Knowledge Distillation".
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
Code for EMNLP 2021 paper Contrastive Out-of-Distribution Detection for Pretrained Transformers.
Contra-OOD Code for EMNLP 2021 paper Contrastive Out-of-Distribution Detection for Pretrained Transformers. Requirements PyTorch Transformers datasets