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
metadata
license: apache-2.0
datasets:
- nvidia/Nemotron-PII
language:
- en
base_model:
- openai/privacy-filter
pipeline_tag: token-classification
library_name: transformers
tags:
- MLX
- NER