README.md

metadata

title: OppaiOracle
emoji: ⚡
colorFrom: pink
colorTo: purple
sdk: gradio
sdk_version: 6.14.0
python_version: '3.12'
app_file: app.py
pinned: false
license: apache-2.0
short_description: Multi-label anime tagger — ViT, 19,294 tags
models:
  - Grio43/OppaiOracle
tags:
  - anime
  - anime-tagger
  - tagger
  - image-tagging
  - multi-label
  - multi-label-classification
  - vision-transformer
  - vit
  - illustration
  - danbooru

OppaiOracle — live demo

Multi-label tagger for anime / illustration images. ViT trained from scratch on a ~5.9M-image cleaned corpus, predicting over 19,000 tags.

• Model card: Grio43/OppaiOracle
• License: Apache 2.0
• Checkpoint served here: V1.1 (448×448 fine-tune of V1)
• Native input resolution: 448×448 (letterboxed)

How to use

1. Drop or upload an anime / illustration image.
2. The Space returns the predicted tags with their probabilities. Per-tag thresholds from pr_thresholds.json are applied where available.
3. Treat the output as a first pass — see the model card for the limitations, especially around color, hair-length, size-bucket, and small-accessory tags.

Notes

• This Space runs the V1.1 ONNX checkpoint via ONNX Runtime on the assigned hardware (ZeroGPU when available, CPU fallback otherwise).
• For local inference (ONNX Runtime, DirectML, CUDA EP), grab V1.1_onnx/model.onnx from the model repo (or V1_onnx/model.onnx if you want the 320×320 sibling).
• For PyTorch / custom inference, grab V1.1_safetensors/model.safetensors plus config.json and preprocessing.json.