privacy filter multilingual — GGUF (F16 + Q8 0) GGUF conversion of OpenMed/privacy filter multilingual , a multilingual PII token classification model (a fine tune of openai/privacy filter ). It labels every token with a BIOES tag over 54 PII categories (217 classes) across 16 languages , so it can be served locally with no Python as the encoder/NER tier of a PII redactor. 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. Runtimes This GGUF uses a custom architecture, openai privacy filter , that is not (yet) part of upstream llama.cpp. It runs on: 1. privacy filter.cpp (recommended) — a small standalone GGML engine for exactly this model family, on stock upstream ggml with no patches (CPU / CUDA / Vulkan). This is the reference runtime and what the parity numbers below are measured against. It exposes a flat C API ( pf load / pf classify → entity spans with UTF 8 byte offsets; pf tokenize / pf logits ) shaped for FFI — see the repo README. 2. LocalAI — install from the model gallery; LocalAI serves it behind the gRPC TokenClassify RPC and runs the constrained…
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