Instructions to use TensorGreed/brewslm-sensitive-data-tagger with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TensorGreed/brewslm-sensitive-data-tagger with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="TensorGreed/brewslm-sensitive-data-tagger")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("TensorGreed/brewslm-sensitive-data-tagger") model = AutoModelForTokenClassification.from_pretrained("TensorGreed/brewslm-sensitive-data-tagger", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
18 days ago
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Card: for education only, no claim to subject-matter expertise; links to BrewSLM and the build write-up
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21 days ago
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Card: not-a-compliance-guarantee limitation; manifest: drop local absolute paths
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24 days ago
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BrewSLM export 37: sensitive-data span tagger, run #143 (deberta-v3-base, 30 types)
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