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[Bugfix] Add use_cross_encoder flag to use correct activation in ClassifierPooler (#20527)

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Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>
This commit is contained in:
Cyrus Leung
2025-07-07 05:01:48 +08:00
committed by GitHub
parent 9528e3a05e
commit c18b3b8e8b
8 changed files with 56 additions and 41 deletions
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5
vllm/model_executor/models/roberta.py
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@@ -18,8 +18,6 @@ from vllm.model_executor.models.bert import BertEmbeddingModel, BertModel
from vllm.model_executor.models.utils import WeightsMapper, maybe_prefix
from vllm.model_executor.pooling_metadata import PoolingMetadata
from vllm.sequence import IntermediateTensors, PoolerOutput
from vllm.transformers_utils.config import (
get_cross_encoder_activation_function)
from .bert_with_rope import BertWithRope, JinaRobertaModel
from .interfaces import SupportsCrossEncoding, SupportsV0Only
@@ -178,9 +176,6 @@ class RobertaForSequenceClassification(nn.Module, SupportsCrossEncoding,
super().__init__()
config = vllm_config.model_config.hf_config
self.default_activation_function = \
get_cross_encoder_activation_function(config)
self.num_labels = config.num_labels
self.roberta = BertModel(vllm_config=vllm_config,
prefix=maybe_prefix(prefix, "bert"),