🛠️Build 6 Models for $103 With Hugging Face's ML-Intern
TL;DR
A Hugging Face post shows how to describe a model in HuggingChat and let the ML-Intern agent plan, train, evaluate, and publish it. The author built six models for about $103 total and shares the prompting habits that kept costs down.
A Hugging Face post shows how to describe a model in HuggingChat and let the ML-Intern agent plan, train, evaluate, and publish it. The author built six models for about $103 total and shares the prompting habits that kept costs down.
Key Points
Workflow: write a detailed first prompt, add verified facts, require a baseline, run a smoke test, set a budget, review checkpoints
Citrus Doctor (Qwen3.5-2B) went from 14.9% to 52.8% accuracy for about $1.90
Agate 4-step cut a text-to-image model from 50 steps to 4, GenEval 0.509 to 0.536 versus 0.563 for the teacher
Pocket Rewriter distills a 9B teacher into 0.8B and 2B models with 99.7% valid output
The agent starts with a zero-dollar budget and must ask before paid jobs
Why It Matters
The reusable part is the prompt discipline: baseline first, smoke test second, spending cap always. It turns agentic training from a gamble into a checklist.
Quick Facts
Comments
Be the first to comment
Enjoyed this article?
Get it daily. 7am. Free. Reads in 5 minutes.
Join 3,566 builders reading daily.