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tscholak
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Oct 4, 2025
| hint=FieldHint.architecture, | ||
| ) | ||
| # TODO: ====== Appropriate name?? ====== | ||
| decoder: BlockSequenceConfig = Field( |
| peft=self._peft, | ||
| ) | ||
| # TODO: ====== Appropriate name?? ====== | ||
| self.decoder = self._config.decoder.get_layer( |
| peft=self._peft, | ||
| ) | ||
| # TODO: ====== Hidden dim ====== | ||
| self.adapter = self._config.adapter.get_layer( |
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I don't think we want to make the adapter part of the encoder, because adapter tensor shapes depend on decoder. And we also want to mix and match existing pre trained encoders and decoders...
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It's the same with every module basically, their shapes all need to match. I'm organizing the modules so thy manage their internal hidden shapes, but input and output shapes are managed by the parent modules (hidden_dim argument), so in that case it makes sense to keep the adapter here.
The todo refers to the MLP assuming matching input and output dimensions, that's an easy fix but I haven't gotten to it yet.
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✨ Description
An attempt at integrating multimodal vision models to main. Still a lot of work to do...