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[Bugfix] model_max_length should consider max_model_len in tokenizer_config (#19201)

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wang.yuqi
2025-06-08 22:17:53 +08:00
committed by GitHub
parent cda10fa3e2
commit 2ffb9b6e07
2 changed files with 30 additions and 1 deletions
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15
vllm/config.py
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@ -44,7 +44,8 @@ from vllm.transformers_utils.config import (
ConfigFormat, get_config, get_hf_image_processor_config,
get_hf_text_config, get_pooling_config,
get_sentence_transformer_tokenizer_config, is_encoder_decoder,
try_get_generation_config, try_get_safetensors_metadata, uses_mrope)
try_get_generation_config, try_get_safetensors_metadata,
try_get_tokenizer_config, uses_mrope)
from vllm.transformers_utils.s3_utils import S3Model
from vllm.transformers_utils.utils import is_s3, maybe_model_redirect
from vllm.utils import (DEFAULT_MAX_NUM_BATCHED_TOKENS,
@ -1427,6 +1428,18 @@ class ModelConfig:
sliding_window_len=self.get_hf_config_sliding_window(),
spec_target_max_model_len=self.spec_target_max_model_len,
encoder_config=self.encoder_config)
tokenizer_config = try_get_tokenizer_config(
self.tokenizer,
trust_remote_code=self.trust_remote_code,
revision=self.tokenizer_revision)
if tokenizer_config is None:
return max_model_len
model_max_length = tokenizer_config.get("model_max_length",
max_model_len)
max_model_len = min(max_model_len, model_max_length)
return max_model_len

16
vllm/transformers_utils/config.py
View File

@ -23,6 +23,7 @@ from transformers.models.auto.image_processing_auto import (
get_image_processor_config)
from transformers.models.auto.modeling_auto import (
MODEL_FOR_CAUSAL_LM_MAPPING_NAMES)
from transformers.models.auto.tokenization_auto import get_tokenizer_config
from transformers.utils import CONFIG_NAME as HF_CONFIG_NAME
from vllm import envs
@ -867,3 +868,18 @@ def try_get_safetensors_metadata(
"Error retrieving safetensors")
except Exception:
return None
def try_get_tokenizer_config(
pretrained_model_name_or_path: Union[str, os.PathLike],
trust_remote_code: bool,
revision: Optional[str] = None,
) -> Optional[dict[str, Any]]:
try:
return get_tokenizer_config(
pretrained_model_name_or_path,
trust_remote_code=trust_remote_code,
revision=revision,
)
except Exception:
return None