Instructions to use moctarsmal/bank-transactions-statements-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moctarsmal/bank-transactions-statements-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="moctarsmal/bank-transactions-statements-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("moctarsmal/bank-transactions-statements-classification") model = AutoModelForSequenceClassification.from_pretrained("moctarsmal/bank-transactions-statements-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ff11c6b3212cd593a032ecbc61662410921a8a1bcfb0f16374e72c396e1b94cb
- Size of remote file:
- 4.09 kB
- SHA256:
- 564335d5ff68a8464f63b3fdd6c1a8076f4dec2529a11c596e18d51823927dbe
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