Update README.md

README.md

@@ -3,8 +3,11 @@ license: mit
 tags:
 - generative model
 - unconditional image generation
-duplicated_from: dg845/diffusers-cd_bedroom256_lpips
+- consistency-model
 ---
+
+**Disclaimer**: This model was added by the amazing community contributor [dg845](https://huggingface.co/dg845) ❤️
+
 Consistency models are a new class of generative models introduced in ["Consistency Models"](https://arxiv.org/abs/2303.01469) ([paper](https://arxiv.org/pdf/2303.01469.pdf), [code](https://github.com/openai/consistency_models)) by Yang Song, Prafulla Dhariwal, Mark Chen, and Ilya Sutskever.
 From the paper abstract:
 
@@ -42,7 +45,7 @@ The `diffusers` pipeline for the `cd_bedroom256_lpips` model can be downloaded a
 ```python
 from diffusers import ConsistencyModelPipeline
 
-pipe = ConsistencyModelPipeline.from_pretrained("dg845/diffusers-cd_bedroom256_lpips")
+pipe = ConsistencyModelPipeline.from_pretrained("openai/diffusers-cd_bedroom256_lpips")
 ```
 
 ## Usage
@@ -58,7 +61,7 @@ from diffusers import ConsistencyModelPipeline
 
 device = "cuda"
 # Load the cd_bedroom256_lpips checkpoint.
-model_id_or_path = "dg845/diffusers-cd_bedroom256_lpips"
+model_id_or_path = "openai/diffusers-cd_bedroom256_lpips"
 pipe = ConsistencyModelPipeline.from_pretrained(model_id_or_path, torch_dtype=torch.float16)
 pipe.to(device)