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:
- f383fac11dacbedfe97fb0c0a942298c095288ab47fd68363f7098384920c4ac
- Size of remote file:
- 218 MB
- SHA256:
- b8097bd0709be92e9f51649283168d385386dd1e8af0fe9c7d92ca75508a5a96
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