Surge AI positions itself as a source of human intelligence for training advanced AI.
AI tools for Machine Learning Engineers
3,775 live tools · ranked by monthly traffic and community votes · dead links removed automatically
Scale AI supplies the data and evaluation services behind many of the world's leading AI models, and it also builds applied AI systems for enterprises and governments.
John Snow Labs Healthcare NLP is a software library of more than 3,000 pretrained models for reading clinical and biomedical text.
TRL, short for Transformers Reinforcement Learning, is a Hugging Face library for post-training transformer language models.
Hyperbolic is a GPU cloud that rents out high-performance compute for training, fine-tuning and serving AI models.
Voyage AI makes embedding models and rerankers that raise the quality of search and retrieval, and it now operates as part of MongoDB.
Amazon SageMaker JumpStart is a machine learning hub inside AWS that gives teams a fast way to find, evaluate and deploy models.
The API powering the AI ecosystem
European AI with open-source roots
AI inference at unprecedented speed
Framework for building with large language models
Run open-source AI without managing servers
Enterprise AI for business language
Production AI infrastructure
CrewAI is a multi-agent platform that covers the full agent lifecycle for businesses: discover what to automate, build agents, govern them in production and optimize them over time.
You're building an AI app and need to run inference without spinning up your own GPU servers
Connect AI to your data
Drag and drop AI
AI coding agent for Jupyter notebooks that generates, executes, and explains data science code from natural language descriptions.
Search that understands meaning
Building AI apps
Synthetic data that doesn't break privacy rules
Ollama is a tool designed to help users quickly and effortlessly set up and utilize large language m
Developers building AI applications for Apple devices face a persistent challenge: running sophisticated models locally without sacrificing speed or draining device resources