Instructions to use bthomas279/scam-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bthomas279/scam-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bthomas279/scam-detector")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bthomas279/scam-detector") model = AutoModelForSequenceClassification.from_pretrained("bthomas279/scam-detector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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- **Developed by:** [bthomas279]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [English]
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- **License:** []
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- **Finetuned from model [optional]:** [More Information Needed]
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### Training Scope
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Here's a list of the types of data used to train V2 of the Scam/Spam Detector:
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- **Developed by:** [bthomas279]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [English]
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- **License:** [cc-by-nc-4.0]
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### Training Scope
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Here's a list of the types of data used to train V2 of the Scam/Spam Detector:
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