Instructions to use m522t/open_groundingdino with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use m522t/open_groundingdino with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="m522t/open_groundingdino")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("m522t/open_groundingdino", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9cddde2f4e2b4c6a79c85059f83bdd121337b2cf114359c2f6ba19a5c1adb498
- Size of remote file:
- 692 MB
- SHA256:
- fedf9c9fb99f394ea159a963a029628839bc50589f9c1c172683c433ff76359c
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