privacy filter nemotron — GGUF (F16 + Q8 0) GGUF conversion of OpenMed/privacy filter nemotron , a fine grained PII token classification model — a fine tune of openai/privacy filter on the nvidia/Nemotron PII dataset. It labels every token with a BIOES tag over 55 PII categories (221 classes) in a single forward pass, then decodes coherent spans with a constrained Viterbi procedure — so it can be served locally with no Python as the encoder/NER tier of a PII redactor. Where the base openai/privacy filter covers 8 coarse categories, this fine tune trades multilingual breadth for category depth : 55 fine grained English categories (first/last name, government IDs, financial, healthcare, vehicle, digital, …). For the full model description, label space, evaluation, limitations, and citations, see the source model card — this card only covers the GGUF packaging and how to run it. For broader language coverage (54 categories across 16 languages) instead of this model's English only depth, see the multilingual fine tune privacy filter multilingual GGUF. Runtimes This GGUF uses a custom architecture, openai privacy filter , that is not (yet) part of upstream llama.cpp. It runs on: 1. priv…
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