Add LoRA support for Cosmos Predict 2.5 and fix pipeline to match official Cosmos repo#13664
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…ncoder attention implementation, and timestep scaling
… to device before torch.stack
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thanks, i left a question
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| device = sample.device | ||
| sigma_t, sigma_s0 = self.sigmas[self.step_index + 1].to(device), self.sigmas[self.step_index].to(device) | ||
| sigma_t, sigma_s0 = self.sigmas[self.step_index + 1], self.sigmas[self.step_index] |
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ohh I think the change here might not be intended, no?
it seeem to have reverted https://github.com/huggingface/diffusers/pull/13489/changes
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thanks, looks good to me once we revert the change in scheculer
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I left some questions and suggestions. LMK if anything is unclear.
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What this PR does
Adds LoRA fine-tuning support for Cosmos Predict 2.5 (nvidia/Cosmos-Predict2.5-2B) and fixes the pipeline to match the official Cosmos reference implementation.
LoRA support
CosmosLoraLoaderMixininsrc/diffusers/loaders/lora_pipeline.pyfor LoRA loading/saving onCosmosTransformer3DModelexamples/cosmos/train_cosmos_predict25_lora.pyusingaccelerate+peftexamples/cosmos/eval_cosmos_predict25_lora.pyCosmosLoraLoaderMixintodocs/source/en/api/loaders/lora.mdFixes to match the official Cosmos repo
conditional_frame_timestepscaling bytimestep_scale=0.001Test plan
check_copies,check_dummies,check_support_list)