Instructions to use microsoft/OmniParser-v2.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/OmniParser-v2.0 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("microsoft/OmniParser-v2.0", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Add YOLOv9-E interactive region detector (#37)
- Add YOLOv9-E interactive region detector (3ad04208583386e8ad1ac2505d245200eee29efd) - Keep only the YOLOv9-E inference weight (ef77ffa0da68a824fd59a2d11215e2862b07b5e9) - Add MIT LICENSE for icon_detect_v3 and document MIT detector weights in model card (9db5ab1e17f2c5182bf0c019cb237127348f3d3b) - Use 0.05 confidence threshold in icon_detect_v3 example to match icon_detect default (9c41f160b9855aa986695f0264a2db9cdf46b28f) - Credit MultimediaTechLab/YOLO (MIT) as the base implementation for icon_detect_v3 (d10c4687d4af8245d67780ae59900f09660aad3a) Co-authored-by: Yadong Lu <adamlu1@users.noreply.huggingface.co>f55d075