Instructions to use PITTI/privacy-filter-nemotron with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PITTI/privacy-filter-nemotron with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="PITTI/privacy-filter-nemotron")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("PITTI/privacy-filter-nemotron") model = AutoModelForTokenClassification.from_pretrained("PITTI/privacy-filter-nemotron", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f0ac45ef12b07750ae632f0070dfed6fd0650eecc669385787d12f43574c8d16
- Size of remote file:
- 5.6 GB
- SHA256:
- 04d51c404b03ec68989f581114629e1692d7620d7aa68f65eea869357db12a35
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