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.
Ask questions to your documents without an internet connection, using the power of LLMs.
Connect your own data sources to a private AI powered tool and start asking in natural language.
PressPulse AI provides machine-learning models, research, training resources, or evaluation tools.
Space emoji (emoji-only character allowed).
A library for machine learning that builds predictions using a linear regression.
A library for machine learning that builds predictions using a linear regression.
Practical Tips for Finetuning LLMs Using LoRA (Low-Rank Adaptation) provides machine-learning models, research, training resources, or evaluation…
A high-speed inference engine for deploying LLMs locally.
Your AI Workspace with Memory: smarter with every use. Your agents learn from every analysis.
Multilingual text (NLP) processing toolkit.
A platform for reproducible and scalable machine learning and deep learning on kubernetes.
Engage with relevant posts, get your posts highlighted for engagement, and distribute them to your audience.
Use AutoML to do model compression.
Python Machine Learning Pentesting Toolbox for Adversarial Attacks. Works with LLMs, DNNs, and other machine learning algorithms.
Production-Ready LLM Agent SDK for Every Developer.
A better version of Jieba, developed by Peking University.
A JavaScript application framework for machine learning and its engineering.
Retrieval Augmented Generation (RAG) framework and context engine powered by Pinecone.
Phrasly AI provides machine-learning models, research, training resources, or evaluation tools.
Machine Learning library for PHP. Algorithms, Cross Validation, Neural Network, Preprocessing, Feature Extraction and much more in one library.
Python library for working with Probabilistic Graphical Models.
A Julia framework for probabilistic graphical models.
Enables single machine or distributed training and evaluation of deep learning models.