Instructions to use Hilbs/Packaging-Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hilbs/Packaging-Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Hilbs/Packaging-Model") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("Hilbs/Packaging-Model") model = AutoModelForImageClassification.from_pretrained("Hilbs/Packaging-Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2c20b252b9517f60339e4a9281c7cdacf7ee4637eab6b5485fc0d4a54f0612cd
- Size of remote file:
- 3.9 kB
- SHA256:
- 68bb8c2d47e87332455df33e52075be6ac0ee04daa3f6fd8e6074c2a72002aac
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