Fazmin/solus_v1_gliner2-privacy-filter-pii-q8

GLiNER2 Privacy Filter PII Multi (q8 ONNX) — Solus v1

The entity extractor behind Solus's PII tools: GLiNER2 Privacy Filter PII Multi, exported to ONNX and quantized to 8 bits.

It is a token classifier built on mdeberta-v3-base, not a generative model. It scores every candidate span in the text against a fixed label set and returns character offsets, so it cannot invent a finding that is not in the input. The label set is baked into the graph at export time: name, address, email, phonenum, idnum, url and username. The encoder's position budget is 512 subwords, so longer text has to be scanned in overlapping windows.

Specifications

Installs as a directory. Every file below is required:

Quantization

Quantization performed at the Faculty of Engineering, McMaster University.

The conversion this build is derived from was produced by okasi, and the weights here are a byte-for-byte copy of that file — the SHA-256 above matches the upstream artifact.

Provenance

• —Original model: fastino/gliner2-privacy-filter-PII-multi
• —Upstream GGUF: okasi/gliner2-privacy-filter-pii-multi-onnx
• —Mirrored for Solus, a desktop app for running language models entirely on your own machine.

Usage

import onnxruntime as ort

session = ort.InferenceSession("model_q8.onnx")

A token classifier, not a generative model. It scores candidate spans against a fixed label set baked into the graph at export time: name, address, email, phone_num, id_num, url, username. Preprocessing and decoding are described in onnx_export_metadata.json; model_q8.onnx.data must sit beside the graph.

License

Licensed Apache-2.0.