Tolga Cangöz
c6ac793955
* Fix typos * chore: Fix typos * chore: Update README.md for promptdiffusion example * Trim trailing white spaces * Fix a typo * update number * chore: update number * Trim trailing white space * Update README.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update README.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> --------- Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
29 lines
1.4 KiB
Markdown
29 lines
1.4 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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# AuraFlow
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AuraFlow is inspired by [Stable Diffusion 3](../pipelines/stable_diffusion/stable_diffusion_3.md) and is by far the largest text-to-image generation model that comes with an Apache 2.0 license. This model achieves state-of-the-art results on the [GenEval](https://github.com/djghosh13/geneval) benchmark.
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It was developed by the Fal team and more details about it can be found in [this blog post](https://blog.fal.ai/auraflow/).
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<Tip>
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AuraFlow can be quite expensive to run on consumer hardware devices. However, you can perform a suite of optimizations to run it faster and in a more memory-friendly manner. Check out [this section](https://huggingface.co/blog/sd3#memory-optimizations-for-sd3) for more details.
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</Tip>
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## AuraFlowPipeline
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[[autodoc]] AuraFlowPipeline
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- all
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- __call__ |