thomas0809

transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

pytorch-image-models

PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNet-V3/V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more

albumentations

Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

attention-is-all-you-need-pytorch

A PyTorch implementation of the Transformer model in "Attention is All You Need".

xlnet

XLNet: Generalized Autoregressive Pretraining for Language Understanding

GLM

GLM (General Language Model)

pet

This repository contains the code for "Exploiting Cloze Questions for Few-Shot Text Classification and Natural Language Inference"

higher

higher is a pytorch library allowing users to obtain higher order gradients over losses spanning training loops rather than individual training steps.

P-tuning

A novel method to tune language models. Codes and datasets for paper ``GPT understands, too''.

pix2seq

Pix2Seq codebase: multi-tasks with generative modeling (autoregressive and diffusion)

FewRel

A Large-Scale Few-Shot Relation Extraction Dataset

Indigo

Universal cheminformatics toolkit, utilities and database search tools

Distributional-Signatures

"Few-shot Text Classification with Distributional Signatures" ICLR 2020

DeepRL-InformationExtraction

Code for the paper "Improving Information Extraction by Acquiring External Evidence with Reinforcement Learning" http://arxiv.org/abs/1603.07954

MolScribe

Robust Molecular Structure Recognition with Image-to-Graph Generation

GraphIE

OChemR

From a chemical reaction image, detect and classify molecules, text and arrows by using the Vision Transformer DETR. Comparisons with well-established CNNs (RetinaNet and FasterRCNN also provided). The detections are then translated into text "OCR" or into SMILES. The direction of the reaction is learned and preserved into the output files.

RxnScribe

A Sequence Generation Model for Reaction Diagram Parsing

Clipboard-to-SMILES-Converter

Converts clipboard content to smiles and much more

DLaaS-Getting-StartedTutorial

This repo is for the IBM MIT AI Lab to use DLaaS in IBM Watson Studio. The demo will use Pytorch to train VGG for CIFAR10. The code is forked from kuangliu (https://github.com/kuangliu/pytorch-cifar) and adapted for submitting the model to IBM Watson Machine Learning on Watson Studio for training. It is meant to get you quick-started. We hope you have some fun running your first models in IBM Cloud