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gliner2-large-v1-onnx-cpu-dynamic-q8 – AI Model by temsa | AlphaNeural AI | AlphaNeural AI

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temsa/
gliner2-large-v1-onnx-cpu-dynamic-q8

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named-entity-recognition

lmo3/gliner2-large-v1-onnx

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GLiNER2 Large ONNX Dynamic Q8 for CPU

This repository contains a dynamic_q8 ONNX Runtime derivative of lmo3/gliner2-large-v1-onnx.

It is intended for CPU inference and for runtimes that select the dynamic_q8 precision entry from gliner2_config.json.

Base model

Upstream model: lmo3/gliner2-large-v1-onnx
Upstream revision: 6adb78ae8098685d239dda324cc124d948962c21
Upstream license: MIT

Quantization

Runtime: ONNX Runtime 1.24.2
Method: dynamic quantization
Weight type: QInt8
Precision key: dynamic_q8
Intended provider: CPUExecutionProvider

Files

onnx/classifier.dynamic_q8.onnx
onnx/count_embed.dynamic_q8.onnx
onnx/encoder.dynamic_q8.onnx
onnx/span_rep.dynamic_q8.onnx
config.json
gliner2_config.json
tokenizer.json
tokenizer_config.json

Notes

The ONNX file names are differentiated, for example onnx/encoder.dynamic_q8.onnx.
gliner2_config.json exposes a dynamic_q8 precision entry pointing at those files.
This export is generated from the upstream fp32 ONNX bundle and is intended as a CPU-oriented derivative.

Analysisserver

Example environment settings:

bash

ANALYSIS_SERVER_MODEL_ID=temsa/gliner2-large-v1-onnx-cpu-dynamic-q8
ANALYSIS_SERVER_MODEL_PRECISION=dynamic_q8