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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c67ff5457c9b068941bb8731170c1bf2aad6f48ef368f9a9269b6032332af4be
- Size of remote file:
- 879 MB
- SHA256:
- e60b85085421b4cd2d93d9b40b5be91d80061e1fd0d684b8ec845739193b4028
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