nutrientdocs/document-classification-demo

Nutrient document classification demo

Open-vocabulary, zero-shot: add candidate classes (a label + optional description per row), upload a document page, and the model ranks them — no fixed class list, no per-class training. Two models, one tab each:

• —v2 flagship — the commercial model (best accuracy).
• —v1 (open-weight) — a downloadable open-vocab classifier.

→ model · leaderboard · benchmark

Secret required

The v2 model is commercial and loaded from a private repo, so this Space needs an HF_TOKEN secret (Settings → Variables and secrets) with read access to it. The weights are used server-side only and are never downloadable. Without the secret, the demo marks the v2 tab unavailable and the open v1 model still runs. Inference runs on ZeroGPU.

Sample document images for quick testing are in examples/.