Instructions to use Jacksss123/net72_uid67 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jacksss123/net72_uid67 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Jacksss123/net72_uid67") 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("Jacksss123/net72_uid67") model = AutoModelForImageClassification.from_pretrained("Jacksss123/net72_uid67") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 364e0c2dc635f4ab245aab35ca820b647c4f0802dab1524d35daee51a0baeddf
- Size of remote file:
- 129 Bytes
- SHA256:
- d2ee4a29eed51b7fb443f30ba31100973bab137ad686f6135561c716eef45e73
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