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condition_embedding_perturbation

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@@ -10,7 +10,7 @@ Code is very simple, add noise during the training loop between the text_encoder
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  perturbation_delta = torch.randn_like(encoder_hidden_states) * (perturbation_deviation)
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  encoder_hidden_states = encoder_hidden_states + perturbation_delta
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- embedding_perturbation is the tunable lambda.
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  Models are SD1.5 trained for 30 epochs, Unet only, AdamW8bit, 2e-6 constant LR, batch size 12. EveryDream2Trainer config json included.
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  perturbation_delta = torch.randn_like(encoder_hidden_states) * (perturbation_deviation)
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  encoder_hidden_states = encoder_hidden_states + perturbation_delta
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+ "embedding_perturbation" is the tunable gamma from the paper.
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  Models are SD1.5 trained for 30 epochs, Unet only, AdamW8bit, 2e-6 constant LR, batch size 12. EveryDream2Trainer config json included.
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