Instructions to use shubhamWi91/train50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shubhamWi91/train50 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="shubhamWi91/train50")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("shubhamWi91/train50") model = AutoModelForObjectDetection.from_pretrained("shubhamWi91/train50") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f925a638c5876301b5c3309982fa4399f971211fcebe44b42f0e42cb7ea5fd60
- Size of remote file:
- 4.09 kB
- SHA256:
- 44179223e7a8f003d07d2ad71e7ed6013483dd7e37818e958ceb7d070ec3e95b
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