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gliner2.5-vllm-cpp
GLiNER2.5 is a zero-shot named entity recognition and structured extraction model. Given a text and a set of label names, it extracts entity spans in a single forward pass — no fine-tuning required. The boundary architecture handles arbitrary span lengths up to the encoded window. In LocalAI, serve via the token classification endpoint with this model. The vllm.cpp engine runs the GLiNER2.5 extraction pipeline through the vllm_gliner_ner C ABI (ABI v27). mDeBERTa-v3-base backbone, 287M params, multilingual, ~594 MB.

Repository: localaiLicense: apache-2.0