Instructions to use fptinters/DocClass-image-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fptinters/DocClass-image-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="fptinters/DocClass-image-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("fptinters/DocClass-image-model") model = AutoModelForImageClassification.from_pretrained("fptinters/DocClass-image-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e3dd2dbad031ec383617e4cfe3fc7dd7a382e5738326c8c56943d5553039c792
- Size of remote file:
- 343 MB
- SHA256:
- 05cbf87455d432152e9977a2ee33345322be9d8c1c4ca8b45501a8a0e4933ae2
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