Instructions to use ZealPyae/linksDetection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZealPyae/linksDetection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ZealPyae/linksDetection")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ZealPyae/linksDetection", dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 373 Bytes
c89f10e 985a5a1 c89f10e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | {
"sklearn": {
"environment": [
"scikit-learn=0.24.2",
"joblib=1.0.1",
"fastapi=0.68.0",
"uvicorn=0.15.0",
"pandas=1.3.3"
],
"example_input": {
"url": "http://example.com"
},
"model": {
"file": "naive_bayes_model.joblib",
"vectorizer": "vectorizer.joblib"
},
"task": "text-classification"
}
}
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