Deploy Aim on Hugging Face Spaces within seconds using the Docker template!
As AI systems get increasingly complex, the ability to effectively debug and monitor them becomes crucial. Use Aim to easily trace complex AI systems built with LangChain.
You can now track your Prophet experiments with Aim! The recent Aim v3.16 release includes a built-in logger object for Prophet runs.
Combining Hugging Face and Aim to make machine learning experiments traceable, reproducible and easier to compare.
Excited to announce Aim v3.16 is out! 🚀
The release of aimlflow sparked user curiosity, a tool that facilitates seamless integration of a powerful experiment tracking user...
We are thrilled to unveil aimlflow, a tool that allows for a smooth integration of a robust experiment tracking UI with MLflow logs! 🚀
A retrospective look at the past year!
We are excited to announce the release of aimlflow, an integration that helps to seamlessly run a powerful experiment tracking UI on MLflow logs! 🎉