Instructions to use saifyxpro/revpass-single with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use saifyxpro/revpass-single with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("saifyxpro/revpass-single") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
π‘οΈ Revpass-Single (YOLOv26s-cls)
Revpass-Single is a highly optimized single-tile classifier designed to identify reCAPTCHA v2 tile contents. It is a core component of the Revpass AI solver system.
π Performance
- Model Architecture: YOLOv26s-cls (Medium)
- Top-2 Accuracy: 90.0% (Verified on Stratified Validation Set)
- Use Case: Filtering "Best Match" tiles for 4x4 grids.
π Usage
from ultralytics import YOLO
# Load the model
model = YOLO("[https://huggingface.co/saifyxpro/revpass-single/resolve/main/revpass-single.pt](https://huggingface.co/saifyxpro/revpass-single/resolve/main/revpass-single.pt)")
# Inference
results = model("path/to/tile.jpg")
print(results[0].probs.top1conf)
π Files
revpass-single.pt: PyTorch weights (Best).
revpass-single.onnx: ONNX export for high-performance inference.
Generated by Revpass Auto-Trainer
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