README.md

---

title: WD EVA02 LoRA ONNX Tagger
emoji: 🖼️
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: 4.28.3 # Make sure this matches your gradio version
app_file: app.py
license: apache-2.0 # または適切なライセンス
# Pinned Hardware: T4 small (GPU) or CPU upgrade (CPU)
# pinned: false # 必要に応じてTrueに
# hardware: cpu-upgrade # or cuda-t4-small
# hf_token: YOUR_HF_TOKEN # Use secrets instead!
---


# WD EVA02 LoRA ONNX Tagger

This Space demonstrates image tagging using a fine-tuned WD EVA02 model (converted to ONNX format).

Model Repository: [celstk/wd-eva02-lora-onnx](https://huggingface.co/celstk/wd-eva02-lora-onnx)

**How to Use:**
1. Upload an image using the upload button.
2. Alternatively, paste an image URL into the browser (experimental paste handling).
3. Adjust the tag thresholds if needed.
4. Choose the output mode (Tags only or include visualization).
5. Click the "Predict" button.

**Note:**
- This Space uses a model from a **private** repository (`celstk/wd-eva02-lora-onnx`). You might need to duplicate this space and add your Hugging Face token (`HF_TOKEN`) to the Space secrets to allow downloading the model files.
- Image pasting behavior might vary across browsers.
- If you require GPU acceleration, uncomment the `hardware: cuda-t4-small` line above and ensure the environment has the necessary CUDA libraries compatible with `onnxruntime-gpu`. The current setup defaults to CPU due to potential CUDA library mismatches in the standard Spaces environment.