Instructions to use fedihch/InvoiceReceiptClassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fedihch/InvoiceReceiptClassifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="fedihch/InvoiceReceiptClassifier") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("fedihch/InvoiceReceiptClassifier") model = AutoModelForSequenceClassification.from_pretrained("fedihch/InvoiceReceiptClassifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 676a2b01678d38e4b804e537e5b69c46b43f93552b9cef543126d4ca4b71fb0a
- Size of remote file:
- 802 MB
- SHA256:
- 5849f1cdca8e5afbac3ccdf10cbf4d2e558bbeb4ab63f7ac28bbed6b0099f8d8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.