ml-intern
Hugging Face's AI agent that automates post-training
60 followers
Hugging Face's AI agent that automates post-training
60 followers
An open-source AI agent that fully automates post-training: reads arXiv papers, fixes & creates datasets, runs training jobs, debugs failures, and iterates all by itself. Results: +22 pts on GPQA in 10h and +60% on HealthBench. The future of ML research is here.
I really like that this runs on the smolagents framework and is model-agnostic. One question tho, how does the agent prioritize between conflicting documentation , when two papers provide opposite methods , does it rely strictly on the llm’s reasoning from the standard looping sessions, or is there a specific steering mechanism to decide? Also using JSONL datasets for session observability will be incredibly handy for debugging these complex local runs , gonna experiment now...
Hey everyone!
So I was basically building a fruad detection model using isolation forests. The part that took me hours was feature engineering iterations and retraining after adding new behavioral signals.
I would love to have an agent that reads the relevant papers, fixes the dataset issues, and returns training jobs without literally babysitting.
Though I had some questions like how does it handle domain specific tabular fraud data vs the benchmark tasks it's been tested on?
Awesome tool! Thanks for releasing it, I’ve been using it non stop in the past two days🫶