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from transformers.configuration_utils import PretrainedConfig
from transformers.models.qwen2_5_vl.configuration_qwen2_5_vl import Qwen2_5_VLVisionConfig
from transformers.models.qwen2.configuration_qwen2 import Qwen2Config
class OpenCUAConfig(PretrainedConfig):
"""OpenCUA-2.5-32B model configuration.
Args:
vision_config: Configuration for the vision model.Qwen2_5_VLVisionConfig
text_config: Configuration for the text model. Qwen2Config
pad_token_id: The token ID to use for padding.
"""
model_type = "opencua"
def __init__(
self,
vision_config: dict | Qwen2_5_VLVisionConfig | None = None,
text_config: dict | Qwen2Config | None = None,
ignore_index: int = -100,
media_placeholder_token_id: int = 151664,
pad_token_id: int = 0,
**kwargs
):
if isinstance(vision_config, dict):
vision_config = Qwen2_5_VLVisionConfig(**vision_config)
self.vision_config = vision_config
if isinstance(text_config, dict):
text_config = Qwen2Config(**text_config)
self.text_config = text_config
self.ignore_index = ignore_index
self.media_placeholder_token_id = media_placeholder_token_id
super().__init__(pad_token_id=pad_token_id, **kwargs)
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