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<!--Copyright 2024 The HuggingFace Team. All rights reserved. | ||
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with | ||
the License. You may obtain a copy of the License at | ||
http://www.apache.org/licenses/LICENSE-2.0 | ||
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on | ||
an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the | ||
specific language governing permissions and limitations under the License. | ||
--> | ||
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# AutoencoderOobleck | ||
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The Oobleck variational autoencoder (VAE) model with KL loss was introduced in [Stability-AI/stable-audio-tools](https://github.com/Stability-AI/stable-audio-tools) and [Stable Audio Open](https://huggingface.co/papers/2407.14358) by Stability AI. The model is used in 🤗 Diffusers to encode audio waveforms into latents and to decode latent representations into audio waveforms. | ||
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The abstract from the paper is: | ||
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*Open generative models are vitally important for the community, allowing for fine-tunes and serving as baselines when presenting new models. However, most current text-to-audio models are private and not accessible for artists and researchers to build upon. Here we describe the architecture and training process of a new open-weights text-to-audio model trained with Creative Commons data. Our evaluation shows that the model's performance is competitive with the state-of-the-art across various metrics. Notably, the reported FDopenl3 results (measuring the realism of the generations) showcase its potential for high-quality stereo sound synthesis at 44.1kHz.* | ||
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## AutoencoderOobleck | ||
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[[autodoc]] AutoencoderOobleck | ||
- decode | ||
- encode | ||
- all | ||
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## OobleckDecoderOutput | ||
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[[autodoc]] models.autoencoders.autoencoder_oobleck.OobleckDecoderOutput | ||
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## OobleckDecoderOutput | ||
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[[autodoc]] models.autoencoders.autoencoder_oobleck.OobleckDecoderOutput | ||
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## AutoencoderOobleckOutput | ||
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[[autodoc]] models.autoencoders.autoencoder_oobleck.AutoencoderOobleckOutput |
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