mudler / mudler/vllm.cpp

Port GLiNER2.5 (fastino/gliner2.5-multi-v1) zero-shot NER to vllm.cpp

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Dominant language
C++
Stars
423
Forks
53
Avg merge
20h 26m
Merged PRs (30d)
310

Description

Port the GLiNER2.5 model (DeBERTa v2 encoder + disentangled attention + GLiNER2 pooler head) into vllm.cpp as the first encoder-only (BERT-class) model. vLLM has no DeBERTa support; the vllm-factory plugin (ddickmann/vllm-factory) is the reference oracle.

Scope: DeBERTa v2 encoder, GLiNER2 pooler head (SpanRep, CountLSTM, classifier), model registration, OpenAI-compatible serving, CPU + GPU (CUDA + ROCm) support, LocalAI backend.

Local issue: ISSUE-LOCAL-01M2TMQF230HKCX03RW6ADCVCT
Row: MODEL-GLINER25
Spec: .agents/specs/gliner2.5.md

Contributor guide

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First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start with .agents/specs/gliner2.5.md and compare the required DeBERTa v2 encoder and GLiNER2 pooler components against the vllm-factory reference oracle. Then trace model registration, OpenAI-compatible serving, and the LocalAI backend; done means the listed CPU, CUDA, ROCm, serving, and registration scope is supported.

Written by the indexing model from the issue text.

Assessment

Tech stack
cpp
Domain
api, backend-api-design, machine-learning
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Active
Clarity
Mostly clear
Newbie friendliness
25/100

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