Purpose

Follow-up to the initial ColBERT support (#33686). Extends vLLM's ColBERT late-interaction support beyond standard BERT to multiple encoder backbones, enabling models like lightonai/GTE-ModernColBERT-v1 (ModernBERT) and jinaai/jina-colbert-v2 (Jina XLM-RoBERTa).

What changed:

• ColBERTMixin — new mixin that extracts all shared ColBERT logic (projection layer init, weight loading, pooler building, colbert_dim auto-detection from config or weight shape). Adding a new backbone is now ~40 lines of code.

• ColBERTModernBertModel — ColBERT with ModernBERT backbone

• ColBERTJinaRobertaModel — ColBERT with Jina XLM-RoBERTa backbone (uses JinaRobertaModel)

• Refactored the existing HF_ColBERT class to use ColBERTMixin internally, keeping backward compatibility

• Minor config plumbing so Jina XLM-RoBERTa and pylate-trained models (e.g. lightonai/GTE-ModernColBERT-v1) are recognized correctly

• Tests are now parametrized across all three backbones (BERT, ModernBERT, Jina) with per-backbone HF comparison tests

• Updated docs with architecture table and usage examples for each backbone

Test Plan

# Unit tests (parametrized across all 3 backbones)
python -m pytest tests/models/language/pooling/test_colbert.py -x -v

# Online endpoint tests (rerank, score, token_embed, embed_not_supported × 3 models)
python -m pytest tests/entrypoints/pooling/score/test_online_colbert.py -x -v


## Test Result

All tests passed