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58 lines
2.0 KiB
Markdown
58 lines
2.0 KiB
Markdown
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
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Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
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the License. You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
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an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
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specific language governing permissions and limitations under the License.
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-->
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# Tiny AutoEncoder
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Tiny AutoEncoder for Stable Diffusion (TAESD) was introduced in [madebyollin/taesd](https://github.com/madebyollin/taesd) by Ollin Boer Bohan. It is a tiny distilled version of Stable Diffusion's VAE that can quickly decode the latents in a [`StableDiffusionPipeline`] or [`StableDiffusionXLPipeline`] almost instantly.
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To use with Stable Diffusion v-2.1:
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```python
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import torch
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from diffusers import DiffusionPipeline, AutoencoderTiny
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pipe = DiffusionPipeline.from_pretrained(
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"stabilityai/stable-diffusion-2-1-base", torch_dtype=torch.float16
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)
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pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesd", torch_dtype=torch.float16)
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pipe = pipe.to("cuda")
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prompt = "slice of delicious New York-style berry cheesecake"
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image = pipe(prompt, num_inference_steps=25).images[0]
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image
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```
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To use with Stable Diffusion XL 1.0
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```python
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import torch
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from diffusers import DiffusionPipeline, AutoencoderTiny
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pipe = DiffusionPipeline.from_pretrained(
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"stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
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)
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pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
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pipe = pipe.to("cuda")
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prompt = "slice of delicious New York-style berry cheesecake"
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image = pipe(prompt, num_inference_steps=25).images[0]
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image
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```
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## AutoencoderTiny
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[[autodoc]] AutoencoderTiny
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## AutoencoderTinyOutput
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[[autodoc]] models.autoencoders.autoencoder_tiny.AutoencoderTinyOutput
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