NNtrainer is Software Framework for Training Neural Network Models on Devices.

Official inference framework for 1-bit LLMs

Codes for papers on Large Language Models Personalization (LaMP)

Official PyTorch implementation of Learning to (Learn at Test Time): RNNs with Expressive Hidden States

The repo for In-context Autoencoder

🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

Official implementation of Half-Quadratic Quantization (HQQ)

We introduce a novel approach for parameter generation, named neural network diffusion (\textbf{p-diff}, p stands for parameter), which employs a standard latent diffusion model to synthesize a new…

GoogleTest - Google Testing and Mocking Framework

A Bayesian approach to PEFT: Sparse Foundation Model Fine-tuning

Code accompanying the ECCV 2020 paper "Trajectron : Dynamically-Feasible Trajectory Forecasting With Heterogeneous Data" by Tim Salzmann*, Boris Ivanovic*, Punarjay Chakravarty, and Marco Pavone (…

Variational Autoencoder and Conditional Variational Autoencoder on MNIST in PyTorch

End-to-End Object Detection with Transformers for custom dataset are forked from Facebook Research

Pytorch implementation of TrAISformer---A generative transformer for AIS trajectory prediction (https://arxiv.org/abs/2109.03958).

(Fork Manh's directory for submission)_ 제출용

This is the official PyTorch implementation of the paper "TransFG: A Transformer Architecture for Fine-grained Recognition" (Ju He, Jie-Neng Chen, Shuai Liu, Adam Kortylewski, Cheng Yang, Yutong Ba…

PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations

[CVPR 2022] CoTTA Code for our paper Continual Test-Time Domain Adaptation

[ICCV 2021] Target Adaptive Context Aggregation for Video Scene Graph Generation

Explainability for Vision Transformers

Spatial-Temporal Transformer for Dynamic Scene Graph Generation, ICCV2021

PyTorch implementation of MoCo v3 https//arxiv.org/abs/2104.02057

The official PyTorch code implementation of "Personalized Trajectory Prediction via Distribution Discrimination" in ICCV 2021.

Source code "Unsupervised Model Personalization while Preserving Privacy and Scalability: An Open Problem." @ CVPR2020

A collection of AWESOME things about domian adaptation