latent-consistency
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lcm-lora-sdv1-5

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patrickvonplaten commited on Nov 9, 2023

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@@ -35,14 +35,14 @@ pip install --upgrade diffusers transformers accelerate peft
 ### Text-to-Image
-The adapter can be loaded with it's base model `runwayml/stable-diffusion-v1-5`. Next, the scheduler needs to be changed to [`LCMScheduler`](https://huggingface.co/docs/diffusers/v0.22.3/en/api/schedulers/lcm#diffusers.LCMScheduler) and we can reduce the number of inference steps to just 2 to 8 steps.
 Please make sure to either disable `guidance_scale` or use values between 1.0 and 2.0.
 ```python
 import torch
 from diffusers import LCMScheduler, AutoPipelineForText2Image
-model_id = "runwayml/stable-diffusion-v1-5"
 adapter_id = "latent-consistency/lcm-lora-sdv1-5"
 pipe = AutoPipelineForText2Image.from_pretrained(model_id, torch_dtype=torch.float16, variant="fp16")

 ### Text-to-Image
+The adapter can be loaded with SDv1-5 or deviratives. Here we use `Lykon/dreamshaper-7`. Next, the scheduler needs to be changed to [`LCMScheduler`](https://huggingface.co/docs/diffusers/v0.22.3/en/api/schedulers/lcm#diffusers.LCMScheduler) and we can reduce the number of inference steps to just 2 to 8 steps.
 Please make sure to either disable `guidance_scale` or use values between 1.0 and 2.0.
 ```python
 import torch
 from diffusers import LCMScheduler, AutoPipelineForText2Image
+model_id = "Lykon/dreamshaper-7"
 adapter_id = "latent-consistency/lcm-lora-sdv1-5"
 pipe = AutoPipelineForText2Image.from_pretrained(model_id, torch_dtype=torch.float16, variant="fp16")