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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from austinb/fraud_text_detection: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
-
https://huggingface.co/austinb/fraud_text_detection/resolve/main/tokenizer.json
- Command line
-
hf download hf://austinb/fraud_text_detection/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/austinb/fraud_text_detection/resolve/main/tokenizer.json
712 kB
File too large to display, you can check the raw version instead.