Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Recently added
Recently added to the directory
Browse dated community launches and imported or editorial directory additions.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Reading Wikipedia to answer open-domain questions.
DressMe.AI provides machine-learning models, research, training resources, or evaluation tools.
Python library for scalable Bayesian optimisation.
Many useful features that aren't part of the main nn package.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Shared knowledge makes agents faster and more reliable.
Free AI domain generator with availability check and price comparison.
Databricks’ Dolly, a large language model trained on the Databricks Machine Learning Platform.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Docs provides machine-learning models, research, training resources, or evaluation tools.
DocketAI — built on Replit. Update this description to reflect the app.
DLib has C++ and Python interfaces for face detection and training general object detectors.
A deep learning-based translation library between 50 languages, built with transformers.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Distill provides machine-learning models, research, training resources, or evaluation tools.
The Deep Learning GPU Training System (DIGITS) is a web application for training deep learning models.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
DiffSharp provides machine-learning models, research, training resources, or evaluation tools.
. Practical AI engineering and generative AI explained simply: RAG, agents, and LLM application patterns for builders.
Deep learning in Rust, with shape checked tensors and neural networks.