Update README.md

README.md

@@ -8,12 +8,12 @@ license: openrail++
 inference: false
 ---
 
-# Latent Consistency Model (LCM) LoRA: SDv1-5
+# Latent Consistency Model (LCM) LoRA: SSD-1B
 
 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.*
 
-It is a distilled consistency adapter for [`runwayml/stable-diffusion-v1-5`](https://huggingface.co/runwayml/stable-diffusion-v1-5) that allows
+It is a distilled consistency adapter for [`segmind/SSD-1B`](https://huggingface.co/runwayml/stable-diffusion-v1-5) that allows
 to reduce the number of inference steps to only between **2 - 8 steps**.
 
 | Model                                                                      | Params / M | 
@@ -35,14 +35,14 @@ pip install --upgrade diffusers transformers accelerate peft
 
 ### Text-to-Image
 
-The adapter can be loaded with SDv1-5 or deviratives. Here we use [`Lykon/dreamshaper-7`](https://huggingface.co/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.
+Let's load the base model `segmind/SSD-1B` first. 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"
+model_id = "segmind/SSD-1B"
 adapter_id = "latent-consistency/lcm-lora-sdv1-5"
 
 pipe = AutoPipelineForText2Image.from_pretrained(model_id, torch_dtype=torch.float16, variant="fp16")