Peng Tang's starred repositories
transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
segment-anything
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
PaddleOCR
Awesome multilingual OCR toolkits based on PaddlePaddle (practical ultra lightweight OCR system, support 80+ languages recognition, provide data annotation and synthesis tools, support training and deployment among server, mobile, embedded and IoT devices)
Swin-Transformer
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
Awesome-Diffusion-Models
A collection of resources and papers on Diffusion Models
Transformers-Tutorials
This repository contains demos I made with the Transformers library by HuggingFace.
TensorRT-LLM
TensorRT-LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and build TensorRT engines that contain state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT-LLM also contains components to create Python and C++ runtimes that execute those TensorRT engines.
TextRecognitionDataGenerator
A synthetic data generator for text recognition
awesome-implicit-representations
A curated list of resources on implicit neural representations.
webdataset
A high-performance Python-based I/O system for large (and small) deep learning problems, with strong support for PyTorch.
awesome-instruction-dataset
A collection of open-source dataset to train instruction-following LLMs (ChatGPT,LLaMA,Alpaca)
awesome-chatgpt-dataset
Unlock the Power of LLM: Explore These Datasets to Train Your Own ChatGPT!
pan_pp.pytorch
Official implementations of PSENet, PAN and PAN++.
amazon-textract-textractor
Analyze documents with Amazon Textract and generate output in multiple formats.
pcl.pytorch
PyTorch codes for our papers "Multiple Instance Detection Network with Online Instance Classifier Refinement" and "PCL: Proposal Cluster Learning for Weakly Supervised Object Detection".