General technology for enabling AI capabilities w/ LLMs and MLLMs.
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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.
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.
Deep learning foundations and applications.
C, C++, and Python tools for named entity recognition and relation extraction.
A Julia package for fitting (statistical) mixed-effects models.
Mixtral-8x7B Large Language Model (LLM) is a pretrained generative Sparse Mixture of Experts.
ML Resources supports machine learning models, deployment, inspection, datasets, or AI development workflows.
Machine learning and numerical analysis tools for Node.js and the Browser!
500+ ML/AI interview Q&A with runnable code — covers ML fundamentals, deep learning, NLP, PyTorch, scikit-learn pipelines, and system design.
A set of functions to support the development of machine learning algorithms.
A Julia machine learning framework.
A simple Machine Learning Framework written in Swift. Currently features Simple Linear Regression, Polynomial Regression, and Ridge Regression.
No need to keep checking your training, just one import line and you'll know the second it's done.
A scalable C++ machine learning library.
A library consisting of useful tools for data science and machine learning tasks.
MMDeploy supports machine learning models, deployment, inspection, datasets, or AI development workflows.
A modular active learning framework for Python, built on top of scikit-learn.
Discover open source deep learning code and pretrained models.