Token Classification
Transformers
Safetensors
openai_privacy_filter
privacy
pii
ner
redaction
nemotron
openmed
openai-privacy-filter
Instructions to use OpenMed/privacy-filter-nemotron-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/privacy-filter-nemotron-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/privacy-filter-nemotron-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/privacy-filter-nemotron-v2") model = AutoModelForTokenClassification.from_pretrained("OpenMed/privacy-filter-nemotron-v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ab5d272d3fa3a0f341335e1d90bd8f4b438b0c14a72f07c182703b95abc831e1
- Size of remote file:
- 2.8 GB
- SHA256:
- e27b99207fcc98834100a773037b4b1105f3569a0ced47c91b1538ed599fb645
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