Instructions to use shubhamWi91/train13 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shubhamWi91/train13 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="shubhamWi91/train13")# Load model directly from transformers import AutoModelForObjectDetection model = AutoModelForObjectDetection.from_pretrained("shubhamWi91/train13", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2222dfa72f089b8c0cf96c847e58c64aa60a02aa0ad0e3a27bf47e9198ac45ce
- Size of remote file:
- 879 MB
- SHA256:
- 57e210fd0054426a510038426d8cd21c90103942374515cc77977d32261b5a54
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