MindSpore is a new open source deep learning training/inference framework that could be used for mobile, edge and cloud scenarios.
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Documentation for MiniMax, covering setup, features, and practical usage.
Building AGI with our mission Intelligence with Everyone. Global leader in multi-modal models and AI-native products with over 200 million users.
Full-stack AI platform focused on multimodal agents and consumer-scale deployment.
MiniMax AI helps build, test, automate, or manage AI agents, prompts, models, and API workflows.
Overview of MiniMax AI models and their capabilities.
Self-updating documentation for startups, enterprises, and agents.
Organize your company's data and put agents to work.
Intuitive convenience tooling for lightning-fast, efficient development and ensuring quality in LLM-based applications.
Mistral provides conversational AI for questions, tasks, and general assistance.
Mistral Studio helps build, test, automate, or manage AI agents, prompts, models, and API workflows.
Deep learning foundations and applications.
All-in-one web-based IDE specialized for machine learning and data science.
500+ ML/AI interview Q&A with runnable code — covers ML fundamentals, deep learning, NLP, PyTorch, scikit-learn pipelines, and system design.
Version and deploy your ML models following GitOps principles.
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.
Open source MLOps platform that helps you collaborate, reproduce and share your ML work.
A library consisting of useful tools for data science and machine learning tasks.
Place to meet for humans, agents and NPCs with MCP (Model Context Protocol) client/server integration.
Open-source project that creates or edits images with generative AI and text-based controls.
An open standard for connecting AI models to external tools and data sources. MCP Registry opensource.
Discover open source deep learning code and pretrained models.
Open source ML model versioning, metadata, and experiment management.