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Init for korean docs (huggingface#1910)
* init for korean docs * edit build yml file for multi language docs * edit one more build yml file for multi language docs * add title for get_frontmatter error
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- sections: | ||
- local: index | ||
title: "🧨 Diffusers" | ||
- local: quicktour | ||
title: "훑어보기" | ||
- local: installation | ||
title: "설치" | ||
title: "시작하기" | ||
- sections: | ||
- sections: | ||
- local: in_translation | ||
title: "Loading Pipelines, Models, and Schedulers" | ||
- local: in_translation | ||
title: "Using different Schedulers" | ||
- local: in_translation | ||
title: "Configuring Pipelines, Models, and Schedulers" | ||
- local: in_translation | ||
title: "Loading and Adding Custom Pipelines" | ||
title: "불러오기 & 허브 (번역 예정)" | ||
- sections: | ||
- local: in_translation | ||
title: "Unconditional Image Generation" | ||
- local: in_translation | ||
title: "Text-to-Image Generation" | ||
- local: in_translation | ||
title: "Text-Guided Image-to-Image" | ||
- local: in_translation | ||
title: "Text-Guided Image-Inpainting" | ||
- local: in_translation | ||
title: "Text-Guided Depth-to-Image" | ||
- local: in_translation | ||
title: "Reusing seeds for deterministic generation" | ||
- local: in_translation | ||
title: "Community Pipelines" | ||
- local: in_translation | ||
title: "How to contribute a Pipeline" | ||
title: "추론을 위한 파이프라인 (번역 예정)" | ||
- sections: | ||
- local: in_translation | ||
title: "Reinforcement Learning" | ||
- local: in_translation | ||
title: "Audio" | ||
- local: in_translation | ||
title: "Other Modalities" | ||
title: "Taking Diffusers Beyond Images" | ||
title: "Diffusers 사용법 (번역 예정)" | ||
- sections: | ||
- local: in_translation | ||
title: "Memory and Speed" | ||
- local: in_translation | ||
title: "xFormers" | ||
- local: in_translation | ||
title: "ONNX" | ||
- local: in_translation | ||
title: "OpenVINO" | ||
- local: in_translation | ||
title: "MPS" | ||
- local: in_translation | ||
title: "Habana Gaudi" | ||
title: "최적화/특수 하드웨어 (번역 예정)" | ||
- sections: | ||
- local: in_translation | ||
title: "Overview" | ||
- local: in_translation | ||
title: "Unconditional Image Generation" | ||
- local: in_translation | ||
title: "Textual Inversion" | ||
- local: in_translation | ||
title: "Dreambooth" | ||
- local: in_translation | ||
title: "Text-to-image fine-tuning" | ||
title: "학습 (번역 예정)" | ||
- sections: | ||
- local: in_translation | ||
title: "Stable Diffusion" | ||
- local: in_translation | ||
title: "Philosophy" | ||
- local: in_translation | ||
title: "How to contribute?" | ||
title: "개념 설명 (번역 예정)" | ||
- sections: | ||
- sections: | ||
- local: in_translation | ||
title: "Models" | ||
- local: in_translation | ||
title: "Diffusion Pipeline" | ||
- local: in_translation | ||
title: "Logging" | ||
- local: in_translation | ||
title: "Configuration" | ||
- local: in_translation | ||
title: "Outputs" | ||
title: "Main Classes" | ||
|
||
- sections: | ||
- local: in_translation | ||
title: "Overview" | ||
- local: in_translation | ||
title: "AltDiffusion" | ||
- local: in_translation | ||
title: "Cycle Diffusion" | ||
- local: in_translation | ||
title: "DDIM" | ||
- local: in_translation | ||
title: "DDPM" | ||
- local: in_translation | ||
title: "Latent Diffusion" | ||
- local: in_translation | ||
title: "Unconditional Latent Diffusion" | ||
- local: in_translation | ||
title: "PaintByExample" | ||
- local: in_translation | ||
title: "PNDM" | ||
- local: in_translation | ||
title: "Score SDE VE" | ||
- sections: | ||
- local: in_translation | ||
title: "Overview" | ||
- local: in_translation | ||
title: "Text-to-Image" | ||
- local: in_translation | ||
title: "Image-to-Image" | ||
- local: in_translation | ||
title: "Inpaint" | ||
- local: in_translation | ||
title: "Depth-to-Image" | ||
- local: in_translation | ||
title: "Image-Variation" | ||
- local: in_translation | ||
title: "Super-Resolution" | ||
title: "Stable Diffusion" | ||
- local: in_translation | ||
title: "Stable Diffusion 2" | ||
- local: in_translation | ||
title: "Safe Stable Diffusion" | ||
- local: in_translation | ||
title: "Stochastic Karras VE" | ||
- local: in_translation | ||
title: "Dance Diffusion" | ||
- local: in_translation | ||
title: "UnCLIP" | ||
- local: in_translation | ||
title: "Versatile Diffusion" | ||
- local: in_translation | ||
title: "VQ Diffusion" | ||
- local: in_translation | ||
title: "RePaint" | ||
- local: in_translation | ||
title: "Audio Diffusion" | ||
title: "파이프라인 (번역 예정)" | ||
- sections: | ||
- local: in_translation | ||
title: "Overview" | ||
- local: in_translation | ||
title: "DDIM" | ||
- local: in_translation | ||
title: "DDPM" | ||
- local: in_translation | ||
title: "Singlestep DPM-Solver" | ||
- local: in_translation | ||
title: "Multistep DPM-Solver" | ||
- local: in_translation | ||
title: "Heun Scheduler" | ||
- local: in_translation | ||
title: "DPM Discrete Scheduler" | ||
- local: in_translation | ||
title: "DPM Discrete Scheduler with ancestral sampling" | ||
- local: in_translation | ||
title: "Stochastic Kerras VE" | ||
- local: in_translation | ||
title: "Linear Multistep" | ||
- local: in_translation | ||
title: "PNDM" | ||
- local: in_translation | ||
title: "VE-SDE" | ||
- local: in_translation | ||
title: "IPNDM" | ||
- local: in_translation | ||
title: "VP-SDE" | ||
- local: in_translation | ||
title: "Euler scheduler" | ||
- local: in_translation | ||
title: "Euler Ancestral Scheduler" | ||
- local: in_translation | ||
title: "VQDiffusionScheduler" | ||
- local: in_translation | ||
title: "RePaint Scheduler" | ||
title: "스케줄러 (번역 예정)" | ||
- sections: | ||
- local: in_translation | ||
title: "RL Planning" | ||
title: "Experimental Features" | ||
title: "API (번역 예정)" |
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<!--Copyright 2022 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 | ||
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 | ||
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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# 번역중 | ||
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열심히 번역을 진행중입니다. 조금만 기다려주세요. | ||
감사합니다! |
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<!--Copyright 2022 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 | ||
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 | ||
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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<p align="center"> | ||
<br> | ||
<img src="https://raw.githubusercontent.com/huggingface/diffusers/77aadfee6a891ab9fcfb780f87c693f7a5beeb8e/docs/source/imgs/diffusers_library.jpg" width="400"/> | ||
<br> | ||
</p> | ||
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# 🧨 Diffusers | ||
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🤗 Diffusers는 사전학습된 비전 및 오디오 확산 모델을 제공하고, 추론 및 학습을 위한 모듈식 도구 상자 역할을 합니다. | ||
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보다 정확하게, 🤗 Diffusers는 다음을 제공합니다: | ||
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- 단 몇 줄의 코드로 추론을 실행할 수 있는 최신 확산 파이프라인을 제공합니다. ([**Using Diffusers**](./using-diffusers/conditional_image_generation)를 살펴보세요) 지원되는 모든 파이프라인과 해당 논문에 대한 개요를 보려면 [**Pipelines**](#pipelines)을 살펴보세요. | ||
- 추론에서 속도 vs 품질의 절충을 위해 상호교환적으로 사용할 수 있는 다양한 노이즈 스케줄러를 제공합니다. 자세한 내용은 [**Schedulers**](./api/schedulers/overview)를 참고하세요. | ||
- UNet과 같은 여러 유형의 모델을 end-to-end 확산 시스템의 구성 요소로 사용할 수 있습니다. 자세한 내용은 [**Models**](./api/models)을 참고하세요. | ||
- 가장 인기있는 확산 모델 테스크를 학습하는 방법을 보여주는 예제들을 제공합니다. 자세한 내용은 [**Training**](./training/overview)를 참고하세요. | ||
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## 🧨 Diffusers 파이프라인 | ||
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다음 표에는 공시적으로 지원되는 모든 파이프라인, 관련 논문, 직접 사용해 볼 수 있는 Colab 노트북(사용 가능한 경우)이 요약되어 있습니다. | ||
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| Pipeline | Paper | Tasks | Colab | ||
|---|---|:---:|:---:| | ||
| [alt_diffusion](./api/pipelines/alt_diffusion) | [**AltDiffusion**](https://arxiv.org/abs/2211.06679) | Image-to-Image Text-Guided Generation | | ||
| [audio_diffusion](./api/pipelines/audio_diffusion) | [**Audio Diffusion**](https://github.com/teticio/audio-diffusion.git) | Unconditional Audio Generation | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/teticio/audio-diffusion/blob/master/notebooks/audio_diffusion_pipeline.ipynb) | ||
| [cycle_diffusion](./api/pipelines/cycle_diffusion) | [**Cycle Diffusion**](https://arxiv.org/abs/2210.05559) | Image-to-Image Text-Guided Generation | | ||
| [dance_diffusion](./api/pipelines/dance_diffusion) | [**Dance Diffusion**](https://github.com/williamberman/diffusers.git) | Unconditional Audio Generation | | ||
| [ddpm](./api/pipelines/ddpm) | [**Denoising Diffusion Probabilistic Models**](https://arxiv.org/abs/2006.11239) | Unconditional Image Generation | | ||
| [ddim](./api/pipelines/ddim) | [**Denoising Diffusion Implicit Models**](https://arxiv.org/abs/2010.02502) | Unconditional Image Generation | | ||
| [latent_diffusion](./api/pipelines/latent_diffusion) | [**High-Resolution Image Synthesis with Latent Diffusion Models**](https://arxiv.org/abs/2112.10752)| Text-to-Image Generation | | ||
| [latent_diffusion](./api/pipelines/latent_diffusion) | [**High-Resolution Image Synthesis with Latent Diffusion Models**](https://arxiv.org/abs/2112.10752)| Super Resolution Image-to-Image | | ||
| [latent_diffusion_uncond](./api/pipelines/latent_diffusion_uncond) | [**High-Resolution Image Synthesis with Latent Diffusion Models**](https://arxiv.org/abs/2112.10752) | Unconditional Image Generation | | ||
| [paint_by_example](./api/pipelines/paint_by_example) | [**Paint by Example: Exemplar-based Image Editing with Diffusion Models**](https://arxiv.org/abs/2211.13227) | Image-Guided Image Inpainting | | ||
| [pndm](./api/pipelines/pndm) | [**Pseudo Numerical Methods for Diffusion Models on Manifolds**](https://arxiv.org/abs/2202.09778) | Unconditional Image Generation | | ||
| [score_sde_ve](./api/pipelines/score_sde_ve) | [**Score-Based Generative Modeling through Stochastic Differential Equations**](https://openreview.net/forum?id=PxTIG12RRHS) | Unconditional Image Generation | | ||
| [score_sde_vp](./api/pipelines/score_sde_vp) | [**Score-Based Generative Modeling through Stochastic Differential Equations**](https://openreview.net/forum?id=PxTIG12RRHS) | Unconditional Image Generation | | ||
| [stable_diffusion](./api/pipelines/stable_diffusion/text2img) | [**Stable Diffusion**](https://stability.ai/blog/stable-diffusion-public-release) | Text-to-Image Generation | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/training_example.ipynb) | ||
| [stable_diffusion](./api/pipelines/stable_diffusion/img2img) | [**Stable Diffusion**](https://stability.ai/blog/stable-diffusion-public-release) | Image-to-Image Text-Guided Generation | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/image_2_image_using_diffusers.ipynb) | ||
| [stable_diffusion](./api/pipelines/stable_diffusion/inpaint) | [**Stable Diffusion**](https://stability.ai/blog/stable-diffusion-public-release) | Text-Guided Image Inpainting | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/in_painting_with_stable_diffusion_using_diffusers.ipynb) | ||
| [stable_diffusion_2](./api/pipelines/stable_diffusion_2) | [**Stable Diffusion 2**](https://stability.ai/blog/stable-diffusion-v2-release) | Text-to-Image Generation | | ||
| [stable_diffusion_2](./api/pipelines/stable_diffusion_2) | [**Stable Diffusion 2**](https://stability.ai/blog/stable-diffusion-v2-release) | Text-Guided Image Inpainting | | ||
| [stable_diffusion_2](./api/pipelines/stable_diffusion_2) | [**Stable Diffusion 2**](https://stability.ai/blog/stable-diffusion-v2-release) | Text-Guided Super Resolution Image-to-Image | | ||
| [stable_diffusion_safe](./api/pipelines/stable_diffusion_safe) | [**Safe Stable Diffusion**](https://arxiv.org/abs/2211.05105) | Text-Guided Generation | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ml-research/safe-latent-diffusion/blob/main/examples/Safe%20Latent%20Diffusion.ipynb) | ||
| [stochastic_karras_ve](./api/pipelines/stochastic_karras_ve) | [**Elucidating the Design Space of Diffusion-Based Generative Models**](https://arxiv.org/abs/2206.00364) | Unconditional Image Generation | | ||
| [unclip](./api/pipelines/unclip) | [Hierarchical Text-Conditional Image Generation with CLIP Latents](https://arxiv.org/abs/2204.06125) | Text-to-Image Generation | | ||
| [versatile_diffusion](./api/pipelines/versatile_diffusion) | [Versatile Diffusion: Text, Images and Variations All in One Diffusion Model](https://arxiv.org/abs/2211.08332) | Text-to-Image Generation | | ||
| [versatile_diffusion](./api/pipelines/versatile_diffusion) | [Versatile Diffusion: Text, Images and Variations All in One Diffusion Model](https://arxiv.org/abs/2211.08332) | Image Variations Generation | | ||
| [versatile_diffusion](./api/pipelines/versatile_diffusion) | [Versatile Diffusion: Text, Images and Variations All in One Diffusion Model](https://arxiv.org/abs/2211.08332) | Dual Image and Text Guided Generation | | ||
| [vq_diffusion](./api/pipelines/vq_diffusion) | [Vector Quantized Diffusion Model for Text-to-Image Synthesis](https://arxiv.org/abs/2111.14822) | Text-to-Image Generation | | ||
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**참고**: 파이프라인은 해당 문서에 설명된 대로 확산 시스템을 사용한 방법에 대한 간단한 예입니다. |
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