Update README.md

README.md

@@ -8,7 +8,7 @@ license: openrail++
 inference: false
 ---
 
-# Latent Consistency Model (LCM) LoRA: SDXL
+# Latent Consistency Model (LCM) LoRA: SDv1-5
 
 Latent Consistency Model (LCM) LoRA was proposed in [LCM-LoRA: A universal Stable-Diffusion Acceleration Module](TODO:) 
 by *Simian Luo, Yiqin Tan, Suraj Patil, Daniel Gu et al.*
@@ -35,15 +35,15 @@ pip install --upgrade diffusers transformers accelerate peft
 
 ### Text-to-Image
 
-The adapter can be loaded with it's base model `stabilityai/stable-diffusion-xl-base-1.0`. 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.
+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 = "stabilityai/stable-diffusion-xl-base-1.0"
-adapter_id = "latent-consistency/lcm-lora-sdxl"
+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")
 pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)