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:
- 732243bcc8f84066e336dbd546cd90c6056580170ad93a1ba19e92021f521084
- Size of remote file:
- 4.81 MB
- SHA256:
- 5072e3209a04aa01dbf4db72b8fec52cf8cd06a042c9ba819678e084f7b665d5
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