Hugging Face Blog·· YesterdayPickAI score66
How one developer built six custom models with ML-Intern for about USD 103
The model that didn't exist, so you made it yourself
AI summary
A Hugging Face blog author used the ML-Intern agent in HuggingChat to build six small models by writing detailed prompts that specify datasets, base models, baselines, smoke tests, and spending limits. The projects include a citrus disease vision-language model, a Huggy character LoRA, a camera-angle LoRA, a doodle-to-object LoRA, a 0.8B prompt rewriter, and a 4-step distilled Agate model, with total compute cost of about USD 103. Each project's prompts and public models are linked from the post.
Why it matters
The author shows how prompt structure, baselines, smoke tests, and budget caps shape an agent-driven training workflow, with per-project costs given.
Source: Hugging Face Blog · huggingface.co