[Model] Skip unused Jina V5 output layers - #52037

Purpose

Jina Embeddings V5 models are pooling-only, but their vLLM wrappers inherit
causal-LM classes. Because these wrappers already declare themselves as pooling
models, they bypass the generic pooling adapter that replaces generation-only
output layers. The encoder/nano variant therefore retained an unused
ParallelLMHead with shape [128256, 768].

This change applies the existing pooling-model no_init_weights pattern to
both Jina V5 wrappers, replacing ParallelLMHead and LogitsProcessor with a
StageMissingLayer. The decoder/small checkpoint ties its output head to the
input embedding (VocabParallelEmbedding), so that shared embedding remains
intact.

On an NVIDIA RTX PRO 6000 Blackwell (TP=1), the nano checkpoint's loaded model
state changed as follows:

This removes 187.875 MiB of resident parameters (31.75%) and approximately
188 MiB of post-load CUDA memory. This is a resident-memory result; it is not a
claim that the transient module-construction peak is eliminated.

I searched open vLLM PRs and issues for Jina V5/Embeddings V5 combined with
lm_head, output-layer, and pooling terms and found no direct or semantic
duplicate. #32757 is the already-merged generic pooling mechanism used as the
implementation precedent, not another Jina-specific fix.

AI assistance (OpenAI Codex) was used to help investigate, implement, and test
this change. I reviewed the complete diff and the validation results.

Test Plan

• Load and embed two natural prompts with both the base and patched
  jinaai/jina-embeddings-v5-text-nano checkpoints; compare parameter and
  post-load CUDA memory plus float32 embedding bytes.
• Repeat the embedding comparison with
  jinaai/jina-embeddings-v5-text-small to cover its tied embedding.
• Run the existing Jina pooling-model, adapter, and registry tests, then all
  pre-commit hooks applicable to the changed production file.

Commands:

.venv/bin/python -m pytest -q \
  tests/models/language/pooling/test_jina_embeddings_v5.py \
  tests/models/test_adapters.py \
  'tests/models/test_registry.py::test_registry_imports[JinaEmbeddingsV5Model]'

uvx pre-commit run --files \
  vllm/model_executor/models/jina.py

git diff --check

Test Result

• Pytest: 12 passed.
• Pre-commit: all applicable hooks passed, including Ruff, formatting, mypy,
  SPDX, forbidden-import, and configuration checks.
• Nano real-model A/B:
  • Both runs produced embedding SHA-256
    f355f21e03004acfc86af056b3610282290563ab563dd5f9d04e5768bca06688.
  • Both output vectors had shape [768] and L2 norm 1.0.
  • Resident parameter and CUDA memory reductions are reported above.
• Small real-model A/B:
  • Both runs retained 1,192,099,840 parameter bytes and no independent
    lm_head, confirming the tied input embedding was not removed.
  • Both produced embedding SHA-256
    c740490981d58e61cee407638b98c0ad724674e11341bc94086a7fa19a675942.
  • Both output vectors had shape [1024] and L2 norm 1.0.