Instructions to use phishbot/ScamLLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use phishbot/ScamLLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="phishbot/ScamLLM")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("phishbot/ScamLLM") model = AutoModelForSequenceClassification.from_pretrained("phishbot/ScamLLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8604a65daddda72639558355909a44e6f61f5b1a20ce23a3654064f1bef882c6
- Size of remote file:
- 499 MB
- SHA256:
- 56b935e100a11768ae3670fd37f3de11c41bda9b663c3cc81986128e608451d7
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