Showing 961-980 of 1,015 projects
Tencent Pre-training framework in PyTorch with a pre-trained model zoo for NLP tasks
A comprehensive library for sentiment analysis, text classification, and text adversarial defense, tailored for AI-powered developers.
A PyTorch library for building Factorization Machine models for click-through rate prediction tasks.
PyTorch course and tutorials for developers interested in learning and applying AI/ML tools.
A PyTorch implementation of the original Transformer model with interactive visualizations.
A PyTorch implementation of Temporal Segment Networks (TSN) for video understanding and action recognition.
A PyTorch implementation of the Mean Flows for One-step Generative Modeling paper, for vibe coders building AI tools.
High quality implementations of Deep Reinforcement Learning algorithms written in PyTorch
An implementation of Graph Transformer Networks, a neural network architecture for graph-structured data.
A PyTorch library for attacking and defending deep learning models against adversarial examples.
A Python library for profiling and inspecting memory usage in PyTorch applications.
EnlightenGAN is an AI-powered image enhancement tool that can brighten low-light images without requiring paired supervision.
An extensive benchmark for scientific machine learning, focused on physics-informed neural networks and partial differential equations.
A workshop to understand how large language models (LLMs) are implemented and used in Python and PyTorch.
PixelLib is a Python library for image and video segmentation using deep learning models like Mask R-CNN, DeepLab, and PointRend.
A Python-level JIT compiler designed to make unmodified PyTorch programs faster.
A tutorial course for building AI-powered applications using Stable Diffusion and PyTorch.
PyTorch code for a CVPR 2018 paper on few-shot learning, a technique for training ML models with limited data.
Official implementation of CEBRA, a tool for joint behavioral and neural analysis using learnable latent embeddings.
OmniSafe is an infrastructural framework for accelerating safe reinforcement learning research.
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