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:
- 247c82e8815ce78143c4208a68fee8d34c0daccc9365ef9157b738fc00b8ede8
- Size of remote file:
- 343 MB
- SHA256:
- ab774424513070cea0c5372eb774d0e5f8ed9af30eb1fa3f2547653f53df26c7
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