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train_dreambooth_lora_sdxl.py
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@@ -90,7 +90,11 @@ inference: false
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These are LoRA adaption weights for {base_model}.
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The weights were trained on the concept prompt:
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LoRA for the text encoder was enabled: {train_text_encoder}.
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@@ -114,7 +118,7 @@ To just use the base model, you can run:
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import torch
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from diffusers import DiffusionPipeline, AutoencoderKL
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vae = AutoencoderKL.from_pretrained({vae_path}, torch_dtype=torch.float16)
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pipe = DiffusionPipeline.from_pretrained(
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"stabilityai/stable-diffusion-xl-base-1.0",
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@@ -123,7 +127,7 @@ pipe = DiffusionPipeline.from_pretrained(
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# This is where you load your trained weights
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pipe.load_lora_weights({repo_id})
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pipe.to("cuda")
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These are LoRA adaption weights for {base_model}.
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The weights were trained on the concept prompt:
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`{prompt}`
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Use this keyword to trigger your custom model in your prompts :)
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LoRA for the text encoder was enabled: {train_text_encoder}.
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import torch
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from diffusers import DiffusionPipeline, AutoencoderKL
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vae = AutoencoderKL.from_pretrained('{vae_path}', torch_dtype=torch.float16)
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pipe = DiffusionPipeline.from_pretrained(
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"stabilityai/stable-diffusion-xl-base-1.0",
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)
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# This is where you load your trained weights
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pipe.load_lora_weights('{repo_id}')
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pipe.to("cuda")
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