Showing 36 of 139 projects
A PyTorch library providing state-of-the-art methods for generating visual explanations (Class Activation Maps) for computer vision models.
A low-code declarative framework for building custom LLMs, neural networks, and other AI models with YAML configurations.
A low-code declarative framework for building custom LLMs, neural networks, and other AI models with YAML configurations.
A PyTorch library providing 12+ semantic segmentation model architectures with 800+ pretrained convolutional and transformer-based encoders.
A differentiable computer vision library for PyTorch, providing geometric vision and image processing algorithms for AI workflows.
An elegant PyTorch-based deep reinforcement learning library with modular APIs for both research and application development.
A PyTorch implementation of YOLOv3 for real-time object detection, supporting export to ONNX, CoreML, and TFLite.
A comprehensive resource of deep learning techniques and models for analyzing satellite and aerial imagery.
A Python library for performing data science and machine learning on data without direct access, using remote datasites.
A PyTorch library providing efficient, reusable components for deep learning with 3D data, including mesh operations and differentiable rendering.
An open-source Python toolkit for speaker diarization with state-of-the-art pretrained models and pipelines.
An end-to-end speech processing toolkit for speech recognition, text-to-speech, translation, enhancement, and more.
A deep reinforcement learning library offering high-quality, single-file implementations of algorithms like PPO, DQN, and SAC for research and education.
A Python library for flexible and readable tensor operations across numpy, PyTorch, JAX, TensorFlow, and other frameworks.
Deep Lake is a multimodal data lake and vector store optimized for AI, enabling scalable data management, retrieval, and training for LLM and deep learning applications.
A flexible, scalable deep probabilistic programming library built on PyTorch for universal probabilistic modeling.
A flexible, scalable deep probabilistic programming library built on PyTorch for universal representation of computable probability distributions.
An LLM acceleration library for Intel XPU (GPU, NPU, CPU) to speed up local inference and finetuning of popular models.
A PyTorch-based open-source framework for deep learning in healthcare imaging, providing domain-specific tools and workflows.
A library that enables PyTorch, Chainer, MXNet, and NumPy users to write TensorBoard events with simple function calls.
A Python NLP library from Stanford for tokenization, sentence segmentation, NER, and dependency parsing across 60+ languages.
An open-source NLP framework for building and deploying deep learning dialog systems and chatbots with PyTorch and transformers.
An open course on reinforcement learning with a practical focus, featuring hands-on labs and comprehensive materials for both online and on-campus students.
An open course on reinforcement learning with a practical focus, featuring hands-on labs and comprehensive materials for both online and on-campus students.
An open-source PyTorch toolbox for general 3D object detection, supporting LiDAR, camera, and multi-modal models.
A comprehensive toolset for converting, visualizing, and managing deep learning models across multiple frameworks like TensorFlow, PyTorch, and Caffe.
A PyTorch-based toolbox for LiDAR-based 3D object detection, supporting multiple state-of-the-art models and datasets.
A PyTorch-based toolbox for LiDAR-based 3D object detection, supporting multiple state-of-the-art models and datasets.
Rust bindings for the C++ API of PyTorch, providing thin wrappers around libtorch.
An open-source MLOps platform for building, orchestrating, and deploying production AI pipelines and agents.
An end-to-end framework for building custom AI applications and agents directly integrated with databases.
A fully convolutional neural network for real-time instance segmentation, achieving high speed and accuracy on COCO.
Code repository for the 'Machine Learning with PyTorch and Scikit-Learn' book, providing practical examples and notebooks.
A PyTorch library providing GPU-accelerated tools for 3D deep learning, including differentiable rendering and geometric operations.
A high-level library for training and evaluating neural networks in PyTorch with a flexible engine and event system.
A modular container build system providing the latest AI/ML packages for NVIDIA Jetson and JetPack-L4T.
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