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@sayakpaul sayakpaul commented Dec 10, 2024

What does this PR do?

Fixes #9950.

Currently, it only supports LoRAs having the MMDiT blocks.

@vladmandic possible to test this? We can improve support for the LoRAs involving non-MMDiT blocks as we go.

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@vladmandic
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i'll give it a test.

fyi, we just did a complete lora processing refactoring in sdnext and changed load/apply methods from forward to pre-processing.
we're getting quite a better results and its compatible with offloading and quantization.
and yes, we do have sd35 support as well.
if you want to take a look, code is now fully modularized and avoids silly monkey-patching that was previously present.

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@sayakpaul
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Thanks, Vlad!

raise ValueError("Invalid LoRA checkpoint.")

transformer_state_dict = {k: v for k, v in state_dict.items() if "transformer." in k}
transformer_state_dict = {k: v for k, v in state_dict.items() if k.startswith(f"{self.transformer_name}.")}
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To inform the user about it when load_lora_weights() effectively becomes a no-op.

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github-actions bot commented Jan 9, 2025

This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the contributing guidelines are likely to be ignored.

@github-actions github-actions bot added the stale Issues that haven't received updates label Jan 9, 2025
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Improve SD35 LoRA support to cover most popular LoRA formats

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