Instructions to use shubhamWi91/train32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shubhamWi91/train32 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="shubhamWi91/train32")# Load model directly from transformers import AutoModelForObjectDetection model = AutoModelForObjectDetection.from_pretrained("shubhamWi91/train32", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ef76d5840fedbcf9cef8f16218729b8425176350953c1fafa0bc8f6bf8a065d2
- Size of remote file:
- 879 MB
- SHA256:
- ff6ff0e5e506455d8d39df20a5fe28e1f0b6a7af4951aadd7d62f973dd00b056
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