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:
- e80b2cade20130e6b0cc0511dea3f54f7ccde50d8352cf41e14ed081291c5d34
- Size of remote file:
- 4.22 kB
- SHA256:
- 15a8f17d6f9900b4198920113e77c1faed4705d5ce3d6dd0a4928158d4d9f1fc
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