Showing 561-580 of 1,001 projects
A curated list of awesome compiler projects and papers for tensor computation and deep learning.
Easily compute CLIP embeddings and build a CLIP-based retrieval system with this Jupyter Notebook library.
A generative adversarial network (GAN) model for learning and transferring Chinese character styles.
MUNIT is a deep learning-based method for multimodal unsupervised image-to-image translation, enabling vibe coders to create diverse and stylized images.
Deep learning software for colorizing black and white images with a few clicks.
A PyTorch framework for deep learning on point clouds, with support for various point cloud-related tasks.
An AI-powered tool for training supervised models without manual labeling, using foundation models and multimodal learning.
Implementation of papers in 100 lines of code
A collection of computer vision and AI projects in Python, C++, and embedded systems for developers.
An open-source deep learning toolkit for building Speech-to-Text models and deploying them easily.
AIMET is an open-source library for advanced quantization and compression techniques in trained neural network models.
Open-source agent-based simulation framework for large-scale AI societies and language model experiments
Optical character recognition for Japanese manga comics, built with Python and deep learning.
A dataset for music analysis and research, with support for deep learning and reproducible research.
An easy-to-use natural language processing library built on the Gluon deep learning framework.
A C++ API and server for deep learning that supports popular frameworks like PyTorch, TensorFlow, and XGBoost.
An official implementation of a time series forecasting model using large language models.
A Python library that uses deep learning to automatically remove or add mosaics to images and videos.
A PyTorch-based audio source separation toolkit for researchers and developers working on AI audio applications.
A curated list of resources for text detection/recognition with deep learning methods
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