Text Classification
Transformers
PyTorch
ONNX
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use austinb/fraud_text_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use austinb/fraud_text_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="austinb/fraud_text_detection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("austinb/fraud_text_detection") model = AutoModelForSequenceClassification.from_pretrained("austinb/fraud_text_detection") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:9fa67c10c98af838c17079edae124e39f934b7d698cd82b54b9104641a19cb21
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size 267832560
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