Instructions to use deprem-ml/name_anonymization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deprem-ml/name_anonymization with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="deprem-ml/name_anonymization")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("deprem-ml/name_anonymization") model = AutoModelForTokenClassification.from_pretrained("deprem-ml/name_anonymization") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 09cf5fe8bf23fcdf297ff382a8c2f163bf9cbafc1708d648c179bf393d42bded
- Size of remote file:
- 3.5 kB
- SHA256:
- 4d095bb03a50a602dd1a1d2499d385fd9440fbcad5a9689576891e2f47365632
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