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PRXPipeline.from_pretrained() broken with transformers 5.1.0 #13142
PRXPipeline.from_pretrained() fails when loading the T5GemmaEncoder text encoder component with transformers 5.1.0:
AttributeError: 'T5GemmaConfig' object has no attribute 'attention_dropout'
Root cause
In transformers 5.x, T5GemmaConfig was refactored into a composite config with encoder/decoder sub-configs (T5GemmaModuleConfig). T5GemmaEncoder.__init__ expects flat attributes like config.attention_dropout which only exist on T5GemmaModuleConfig, not on the composite T5GemmaConfig. When the pipeline loads the text encoder via from_pretrained, it passes the composite config instead of the encoder sub-config.
Reproduction
fromdiffusersimportPRXPipelinepipe=PRXPipeline.from_pretrained("Photoroom/prx-1024-t2i-beta")
# AttributeError: 'T5GemmaConfig' object has no attribute 'attention_dropout'
Hi @DavidBert, I ran into this T5Gemma compatibility issue as well. I pulled your branch fix-t5gemma-config and verified that PRXPipeline.from_pretrained() now loads correctly with transformers==5.1.0. The attention_dropout attribute error is resolved on my end. Thanks for the quick fix!
Activity
RohanPatil2 commentedon Feb 18, 2026
Hi @DavidBert, I ran into this T5Gemma compatibility issue as well. I pulled your branch fix-t5gemma-config and verified that PRXPipeline.from_pretrained() now loads correctly with transformers==5.1.0. The attention_dropout attribute error is resolved on my end. Thanks for the quick fix!