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Init for korean docs (huggingface#1910)
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* 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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seriousran authored Jan 4, 2023
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1 change: 1 addition & 0 deletions .github/workflows/build_documentation.yml
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with:
commit_sha: ${{ github.sha }}
package: diffusers
languages: en ko
secrets:
token: ${{ secrets.HUGGINGFACE_PUSH }}
1 change: 1 addition & 0 deletions .github/workflows/build_pr_documentation.yml
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commit_sha: ${{ github.event.pull_request.head.sha }}
pr_number: ${{ github.event.number }}
package: diffusers
languages: en ko
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193 changes: 193 additions & 0 deletions docs/source/ko/_toctree.yml
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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)"
16 changes: 16 additions & 0 deletions docs/source/ko/in_translation.mdx
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<!--Copyright 2022 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.
-->

# 번역중

열심히 번역을 진행중입니다. 조금만 기다려주세요.
감사합니다!
63 changes: 63 additions & 0 deletions docs/source/ko/index.mdx
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<!--Copyright 2022 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.
-->

<p align="center">
<br>
<img src="https://raw.githubusercontent.com/huggingface/diffusers/77aadfee6a891ab9fcfb780f87c693f7a5beeb8e/docs/source/imgs/diffusers_library.jpg" width="400"/>
<br>
</p>

# 🧨 Diffusers

🤗 Diffusers는 사전학습된 비전 및 오디오 확산 모델을 제공하고, 추론 및 학습을 위한 모듈식 도구 상자 역할을 합니다.

보다 정확하게, 🤗 Diffusers는 다음을 제공합니다:

- 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.

## 🧨 Diffusers 파이프라인

다음 표에는 공시적으로 지원되는 모든 파이프라인, 관련 논문, 직접 사용해 볼 수 있는 Colab 노트북(사용 가능한 경우)이 요약되어 있습니다.

| 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 |

**참고**: 파이프라인은 해당 문서에 설명된 대로 확산 시스템을 사용한 방법에 대한 간단한 예입니다.
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