Instructions to use shubhamWi91/train83 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shubhamWi91/train83 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="shubhamWi91/train83")# Load model directly from transformers import AutoModelForObjectDetection model = AutoModelForObjectDetection.from_pretrained("shubhamWi91/train83", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7d14f9a5807abca35d902ae39f976ea4dd8a8b243dfc9258386c2b87bafae7fd
- Size of remote file:
- 4.09 kB
- SHA256:
- 6684834c6f3eb08dc0c6c988957810c79030d70c639d32d440a75b7e3851929e
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