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Directory
Models & Machine Learning
Models and machine learning covers model hubs, research papers, training guides and evaluation tools. The topic mixes practical resources with reference material, so you will find repositories that host downloadable models next to sites that explain how a technique works. Some entries are collections of papers or benchmarks, and others are tutorials that walk through fine-tuning or deployment. It pays to compare the model licence, the training data, the hardware needed and the date of the last update. The field moves quickly, so verify version notes on the source before you build on anything listed here.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Creates, rewrites or summarizes written content with language models.
Official repository to use and implement LLaMA 3.1 models, Meta's state-of-the-art large language models.
An open source robotics benchmark for meta- and multi-task reinforcement learning.
Mexopencv: Collection and a development kit of matlab mex functions for OpenCV library.
A distributed machine learning framework Apache Spark.
JARVIS, a system to connect LLMs with ML community.
General technology for enabling AI capabilities w/ LLMs and MLLMs.
Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"s.
Integrate LLM technology quickly and easily into your apps.
LLM-powered multiagent persona simulation for imagination enhancement and business insights.
List of several machine learning libraries.
MindSpore is a new open source deep learning training/inference framework that could be used for mobile, edge and cloud scenarios.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Minion AI provides machine-learning models, research, training resources, or evaluation tools.
An asynchronous engine for continuous & autonomous machine learning, built for real-time usage.
Intuitive convenience tooling for lightning-fast, efficient development and ensuring quality in LLM-based applications.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Deep learning foundations and applications.
C, C++, and Python tools for named entity recognition and relation extraction.
MITRE ATLAS™ provides machine-learning models, research, training resources, or evaluation tools.
A Julia package for fitting (statistical) mixed-effects models.