Fine-tuning a 1.7B model at 3.2 GB VRAM — building FineTune Studio

FineTune Studio exists because every fine-tuning tutorial I found assumed a rented A100 and a notebook full of half-explained flags. I wanted something a student could run: upload a dataset, validate it, launch a real QLoRA job, watch the loss stream live, then see — not assume — whether the fine-tuned model actually improved.

The numbers that matter

17 backend endpoints, 107 / 107 tests passing.

Base model Qwen3-1.7B, peak VRAM ~3.2 GB.

3 inference paths: local, vLLM, or a Hugging Face Space — pick per deployment.

Fine-tuning a 1.7B model at 3.2 GB VRAM — building FineTune Studio

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