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[Bugfix] Fix Qwen3-VL-Reranker load. (#33298)

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Signed-off-by: wang.yuqi <yuqi.wang@daocloud.io>
Signed-off-by: wang.yuqi <noooop@126.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
(cherry picked from commit abb34ac43a)
This commit is contained in:
wang.yuqi
2026-01-29 16:42:53 +08:00
committed by khluu
parent 39e8b49378
commit 1ed963d43a
6 changed files with 232 additions and 110 deletions
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14
vllm/model_executor/models/adapters.py
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@@ -466,6 +466,7 @@ def load_weights_using_from_2_way_softmax(
language_model = _get_language_model_for_seq_cls(model)
is_vlm = language_model is not model
using_vlm_head = is_vlm and hasattr(language_model, "score")
language_model.lm_head = ParallelLMHead(
text_config.vocab_size, text_config.hidden_size, quant_config=quant_config
@@ -506,14 +507,16 @@ def load_weights_using_from_2_way_softmax(
torch.float32
) - lm_head_weight.data[[false_id]].to(torch.float32)
score_layer = language_model.score if is_vlm else model.score
score_layer = language_model.score if using_vlm_head else model.score
param = score_layer.weight
weight_loader = getattr(param, "weight_loader", default_weight_loader)
weight_loader(param, score_weight)
del language_model.lm_head
score_weight_name = "language_model.score.weight" if is_vlm else "score.weight"
score_weight_name = (
"language_model.score.weight" if using_vlm_head else "score.weight"
)
loaded_weights.add(score_weight_name)
lm_head_name = "lm_head.weight"
@@ -537,6 +540,7 @@ def load_weights_no_post_processing(model, weights: Iterable[tuple[str, torch.Te
language_model = _get_language_model_for_seq_cls(model)
is_vlm = language_model is not model
using_vlm_head = is_vlm and hasattr(language_model, "score")
language_model.lm_head = ParallelLMHead(
text_config.vocab_size, text_config.hidden_size, quant_config=quant_config
@@ -572,14 +576,16 @@ def load_weights_no_post_processing(model, weights: Iterable[tuple[str, torch.Te
token_ids = [tokenizer.convert_tokens_to_ids(t) for t in tokens]
score_weight = language_model.lm_head.weight.data[token_ids]
score_layer = language_model.score if is_vlm else model.score
score_layer = language_model.score if using_vlm_head else model.score
param = score_layer.weight
weight_loader = getattr(param, "weight_loader", default_weight_loader)
weight_loader(param, score_weight)
del language_model.lm_head
score_weight_name = "language_model.score.weight" if is_vlm else "score.weight"
score_weight_name = (
"language_model.score.weight" if using_vlm_head else "score.weight"
)
loaded_weights.add(score_weight_name)
lm_head_name = "lm_head.weight"