DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Обновлено 2024-10-17 20:50:55 +03:00
TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data
Обновлено 2024-10-17 12:09:06 +03:00
Hummingbird compiles trained ML models into tensor computation for faster inference.
Обновлено 2024-10-16 21:50:20 +03:00
Tutel MoE: An Optimized Mixture-of-Experts Implementation
Обновлено 2024-09-13 14:49:34 +03:00
This is an official Pytorch implementation of "Cross View Fusion for 3D Human Pose Estimation, ICCV 2019".
Обновлено 2024-08-31 02:46:56 +03:00
CoCosNet v2: Full-Resolution Correspondence Learning for Image Translation
Обновлено 2024-07-25 14:07:42 +03:00
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
Обновлено 2024-07-03 13:54:08 +03:00
UniSpeech - Large Scale Self-Supervised Learning for Speech
Обновлено 2024-04-05 16:14:48 +03:00
Federated Learning Utilities and Tools for Experimentation
Обновлено 2024-01-11 22:20:09 +03:00
Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"
Обновлено 2024-01-09 18:03:18 +03:00
Accelerate your Neural Architecture Search (NAS) through fast, reproducible and modular research.
Обновлено 2023-12-22 22:29:11 +03:00
A flexible framework for running experiments with PyTorch models in a simulated Federated Learning (FL) environment.
Обновлено 2023-08-11 23:02:52 +03:00
Scalable Attentive Sentence-Pair Modeling via Distilled Sentence Embedding (AAAI 2020) - PyTorch Implementation
Обновлено 2023-07-25 19:48:26 +03:00
Official implementation of "VoxelPose: Towards Multi-Camera 3D Human Pose Estimation in Wild Environment"
Обновлено 2023-07-24 03:45:42 +03:00
a transductive approach for video object segmentation
Обновлено 2023-06-27 15:56:56 +03:00
🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.
Обновлено 2023-06-13 00:30:31 +03:00
🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.
Обновлено 2023-06-13 00:30:31 +03:00
Improving Generalization via Scalable Neighborhood Component Analysis
Обновлено 2023-06-12 22:02:13 +03:00
PyTorch ObjectDetection Modules and ONNX ops
Обновлено 2023-06-12 21:23:12 +03:00
Cross-domain Correspondence Learning for Exemplar-based Image Translation. (CVPR 2020 Oral)
Обновлено 2022-12-07 08:35:12 +03:00
The project is an official implement of our ECCV2018 paper "Simple Baselines for Human Pose Estimation and Tracking(https://arxiv.org/abs/1804.06208)"
Обновлено 2022-11-28 22:11:04 +03:00
Large-scale pretraining for dialogue
Обновлено 2022-10-18 02:41:52 +03:00
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
Обновлено 2022-09-23 02:59:07 +03:00
Lightweight Deep Learning Model Training library based on PyTorch
Обновлено 2022-06-08 20:36:02 +03:00
A PyTorch Graph Neural Network Library
Обновлено 2022-02-01 20:31:29 +03:00
Common PyTorch Modules
Обновлено 2021-10-18 13:52:28 +03:00
Machine learning metrics for distributed, scalable PyTorch applications.
Обновлено 2021-09-14 14:47:59 +03:00