Instructions to use seduerr/anonymizer-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seduerr/anonymizer-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="seduerr/anonymizer-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("seduerr/anonymizer-bert") model = AutoModelForTokenClassification.from_pretrained("seduerr/anonymizer-bert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5e0b021b701b9d71c356e4694481457e7b41e686121edb109aaaa877f3d1f903
- Size of remote file:
- 1.33 GB
- SHA256:
- 6599da272099c7cbba62fe391eb3d53dc96ddbeea57afc2bb639c1148ffd9b88
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