Instructions to use serbanstein/bert_invoice_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use serbanstein/bert_invoice_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="serbanstein/bert_invoice_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("serbanstein/bert_invoice_classifier") model = AutoModelForSequenceClassification.from_pretrained("serbanstein/bert_invoice_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b83c6bb450cea8f8979f8b62b4e062594281eb403eddd5a4b0bffa258847c218
- Size of remote file:
- 438 MB
- SHA256:
- 96f948059eb53972c548b166d9500f3cc5a83e30bbe2037fceba6d2818f9c817
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