Instructions to use gplsi/Aitana-FraudDetection-R-1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gplsi/Aitana-FraudDetection-R-1.0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gplsi/Aitana-FraudDetection-R-1.0")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gplsi/Aitana-FraudDetection-R-1.0") model = AutoModelForSequenceClassification.from_pretrained("gplsi/Aitana-FraudDetection-R-1.0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 72702beb700bdcc89bbb124ad3f877d872ecf042df936de342b5826d0496c86f
- Size of remote file:
- 37 MB
- SHA256:
- 34843a8fb66baf3ad74af453bd472639c6a5dac922d6e23f9c30ae8d6a2cb1af
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