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🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
The world's simplest facial recognition api for Python and the command line
2025年最新总结,阿里,腾讯,百度,美团,头条等技术面试题目,以及答案,专家出题人分析汇总。
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
Graph Neural Network Library for PyTorch
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
Faker is a Python package that generates fake data for you.
A very simple framework for state-of-the-art Natural Language Processing (NLP)
Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch
Style transfer, deep learning, feature transform
🐍 Geometric Computer Vision Library for Spatial AI
Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.
Pytorch implementation of convolutional neural network visualization techniques
Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.
The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
A modular framework for vision & language multimodal research from Facebook AI Research (FAIR)
Benchmarks of approximate nearest neighbor libraries in Python
Model interpretability and understanding for PyTorch
Image augmentation library in Python for machine learning.
Siamese and triplet networks with online pair/triplet mining in PyTorch
TensorFlow (Python API) implementation of Neural Style
A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX
Deep learning software for colorizing black and white images with a few clicks.
A probabilistic programming library for Bayesian deep learning, generative models, based on Tensorflow
Convolutional Neural Networks to predict the aesthetic and technical quality of images.
Library for training machine learning models with privacy for training data