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@@ -3,8 +3,11 @@ license: mit
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  tags:
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  - generative model
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  - unconditional image generation
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- duplicated_from: dg845/diffusers-ct_bedroom256
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  ---
 
 
 
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  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.
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  From the paper abstract:
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@@ -42,7 +45,7 @@ The `diffusers` pipeline for the `ct_bedroom256` model can be downloaded as foll
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  ```python
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  from diffusers import ConsistencyModelPipeline
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- pipe = ConsistencyModelPipeline.from_pretrained("dg845/diffusers-ct_bedroom256")
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  ```
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  ## Usage
@@ -58,7 +61,7 @@ from diffusers import ConsistencyModelPipeline
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  device = "cuda"
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  # Load the ct_bedroom256 checkpoint.
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- model_id_or_path = "dg845/diffusers-ct_bedroom256"
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  pipe = ConsistencyModelPipeline.from_pretrained(model_id_or_path, torch_dtype=torch.float16)
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  pipe.to(device)
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  tags:
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  - generative model
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  - unconditional image generation
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+ - consistency-model
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  ---
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+
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+ **Disclaimer**: This model was added by the amazing community contributor [dg845](https://huggingface.co/dg845) ❤️
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+
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  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.
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  From the paper abstract:
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  ```python
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  from diffusers import ConsistencyModelPipeline
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+ pipe = ConsistencyModelPipeline.from_pretrained("openai/diffusers-ct_bedroom256")
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  ```
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  ## Usage
 
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  device = "cuda"
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  # Load the ct_bedroom256 checkpoint.
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+ model_id_or_path = "openai/diffusers-ct_bedroom256"
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  pipe = ConsistencyModelPipeline.from_pretrained(model_id_or_path, torch_dtype=torch.float16)
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  pipe.to(device)
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