Instructions to use Hieu/scam-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hieu/scam-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Hieu/scam-detection")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Hieu/scam-detection") model = AutoModelForSequenceClassification.from_pretrained("Hieu/scam-detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from Hieu/scam-detection: direct link, hf CLI and curl.
- Browser
- Download file 997 MB
-
https://huggingface.co/Hieu/scam-detection/resolve/main/optimizer.pt
- Command line
-
hf download hf://Hieu/scam-detection/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Hieu/scam-detection/resolve/main/optimizer.pt
997 MB
- Xet hash:
- f018f66c97ea59fc0bade18ac8c9629ec45a9cea4bfc7e45bc4b35418341001d
- Size of remote file:
- 997 MB
- SHA256:
- 3675263aefe1ce3e6f3706d676306100708b2e4b6e0ce90f2df40f6622ffa708
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