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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2dc57a990b8c541e3f7a21157c06511ffe61713b7871f97698e9c499671f4a09
- Size of remote file:
- 5.84 kB
- SHA256:
- 33f8378db2b776ca5ccea1c7f23bb55f2db0dab729578a11003daf76a9cbb0d5
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