Update README.md

README.md

@@ -9,10 +9,17 @@ tags:
 
 # Latent Consistency Models
 
-Official Repository of the paper: *[Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference](https://arxiv.org/abs/2310.04378)*.
+Official Repository of the paper: *[Latent Consistency Models](https://arxiv.org/abs/2310.04378)*.
 
 Project Page: https://latent-consistency-models.github.io
 
+## Try our Hugging Face demos: 
+[![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/SimianLuo/Latent_Consistency_Model)
+
+## Model Descriptions:
+Distilled from [Dreamshaper v7](https://huggingface.co/Lykon/dreamshaper-7) fine-tune of [Stable-Diffusion v1-5](https://huggingface.co/runwayml/stable-diffusion-v1-5) with only 4,000 training iterations (~32 A100 GPU Hours). 
+
+## Generation Results:
 
 <p align="center">
     <img src="teaser.png">
@@ -40,7 +47,7 @@ pip install diffusers transformers accelerate
 from diffusers import DiffusionPipeline
 import torch
 
-pipe = DiffusionPipeline.from_pretrained("SimianLuo/LCM_Dreamshaper_v7", custom_pipeline="latent_consistency_txt2img")
+pipe = DiffusionPipeline.from_pretrained("SimianLuo/LCM_Dreamshaper_v7", custom_pipeline="latent_consistency_txt2img", custom_revision="main")
 
 # To save GPU memory, torch.float16 can be used, but it may compromise image quality.
 pipe.to(torch_device="cuda", torch_dtype=torch.float32)
@@ -50,7 +57,7 @@ prompt = "Self-portrait oil painting, a beautiful cyborg with golden hair, 8k"
 # Can be set to 1~50 steps. LCM support fast inference even <= 4 steps. Recommend: 1~8 steps.
 num_inference_steps = 4 
 
-images = pipe(prompt=prompt, num_inference_steps=num_inference_steps, guidance_scale=8.0, lcm_origin_steps=50, output_type="pil", custom_revision=main).images
+images = pipe(prompt=prompt, num_inference_steps=num_inference_steps, guidance_scale=8.0, lcm_origin_steps=50, output_type="pil").images
 ```
 
 ## BibTeX