[i8n-ja] Translating docs to Japanese

Hi! I'm Yasuna🤗

Let's bring the documentation to all the Japanese-speaking community 🌐.

Who would want to translate? Please follow the 🤗 [TRANSLATING guide](https://github.com/huggingface/diffusers/blob/main/docs/TRANSLATING.md). Here is a list of the files ready for translation. Let us know in this issue if you'd like to translate any, and we'll add your name to the list.

Some notes:

* Please translate using an informal tone (imagine you are talking with a friend about Diffusers 🤗).
* Please translate in a gender-neutral way.
* Add your translations to the folder called `` inside the [source folder](https://github.com/huggingface/diffusers/tree/main/docs/source).
* Register your translation in `/_toctree.yml`; please follow the order of the [English version](https://github.com/huggingface/diffusers/blob/main/docs/source/en/_toctree.yml).
* Once you're finished, open a pull request and tag this issue by including #issue-number in the description, where issue-number is the number of this issue. Please ping @stevhliu for review.
* 🙋 If you'd like others to help you with the translation, you can also post in the 🤗 [forums](https://discuss.huggingface.co/c/discussion-related-to-httpsgithubcomhuggingfacediffusers/63).

* Please write here the name of the md file from the following items you'd like to start to be translated.
(ex. I'd like to start translating TECHNIQUES section/reusing_seeds.md from now!)

Pull Request Format
```
Related to #[issue's no.]

What is this PR about ?

I translated the following files to implified Japanese:

toctree.yml
index.md
installation.md
quick-start.md
git_vs_http.md
repository.md

What should you check ?

Grammar and orthograph
If my pull requests follows GitHub/open source contribution good practices (I am a beginner)
```

Thank you so much for your help! 🤗

# GET STARTED section
- [x] index.md @YasunaCoffee
- [x] installation.md
- [x] quicktour.md
- [x] stable_diffusion.md

# TUTORIALS section
- [ ] autopipeline.md @YasunaCoffee
- [ ] basic_training.md @YasunaCoffee
- [ ] fast_diffusion.md @YasunaCoffee
- [x] tutorial_overview.md @YasunaCoffee
- [ ] using_peft_for_inference.md @YasunaCoffee

# USING-DIFFUSERS section
## LOADING&HUB section
- [ ] loading_overview.md @Prgckwb
- [ ] loading.md @Prgckwb
- [ ] schedulers.md @Prgckwb
- [ ] custom_pipeline_overview.md @Prgckwb
- [ ] using_safetensors.md @Prgckwb
- [ ] other-formats.md @Prgckwb
- [ ] loading_adapters.md @Prgckwb
- [ ] push_to_hub.md @Prgckwb

## TASKS section
- [ ] pipeline_overview.md
- [ ] unconditional_image_generation.md
- [ ] conditional_image_generation.md
- [ ] img2img.md
- [ ] inpaint.md
- [ ] depth2img.md

## TECHNIQUES section
- [ ] textual_inversion_inference.md
- [ ] reusing_seeds.md
- [ ] control_brightness.md
- [ ] weighted_prompts.md
- [ ] freeu.md

# USING DIFFUSERS (SPECIFIC PIPELINE EXAMPLES) section
- [ ] sdxl.md [Stable Diffusion XL](https://huggingface.co/docs/diffusers/using-diffusers/sdxl)
- [ ] sdxl_turbo.md [SDXL Turbo](https://huggingface.co/docs/diffusers/using-diffusers/sdxl_turbo)
- [ ] kandinsky.md [Kandinsky](https://huggingface.co/docs/diffusers/using-diffusers/kandinsky)
- [ ] controlnet.md [ControlNet](https://huggingface.co/docs/diffusers/using-diffusers/controlnet)
- [ ] shap-e.md [Shap-E](https://huggingface.co/docs/diffusers/using-diffusers/shap-e)
- [ ] diffedit.md [DiffEdit](https://huggingface.co/docs/diffusers/using-diffusers/diffedit)
- [ ] distilled_sd.md [Distilled Stable Diffusion inference](https://huggingface.co/docs/diffusers/using-diffusers/distilled_sd)
- [ ] callback.md [Pipeline callbacks](https://huggingface.co/docs/diffusers/using-diffusers/callback)
- [ ] reproducibility.md [Create reproducible pipelines](https://huggingface.co/docs/diffusers/using-diffusers/reproducibility)
- [ ] custom_pipeline_examples.md [Community pipelines](https://huggingface.co/docs/diffusers/using-diffusers/custom_pipeline_examples)
- [ ] contribute_pipeline.md [Contribute a community pipeline](https://huggingface.co/docs/diffusers/using-diffusers/contribute_pipeline)
- [ ] inference_with_lcm_lora.md [Latent Consistency Model-LoRA](https://huggingface.co/docs/diffusers/using-diffusers/inference_with_lcm_lora)
- [ ] inference_with_lcm.md [Latent Consistency Model](https://huggingface.co/docs/diffusers/using-diffusers/inference_with_lcm)
- [ ] svd.md [Stable Video Diffusion](https://huggingface.co/docs/diffusers/using-diffusers/svd)

# TRAINING section
- [ ] overview.md [Overview](https://huggingface.co/docs/diffusers/training/overview)
- [ ] create_dataset.md [Create a dataset for training](https://huggingface.co/docs/diffusers/training/create_dataset)
- [ ] adapt_a_model.md[Adapt a model to a new task](https://huggingface.co/docs/diffusers/training/adapt_a_model)

## MODELS
- [ ] unconditional_training.md[Unconditional image generation](https://huggingface.co/docs/diffusers/training/unconditional_training)
- [ ] text2image.md[Text-to-image](https://huggingface.co/docs/diffusers/training/text2image)
- [ ] sdxl.md[Stable Diffusion XL](https://huggingface.co/docs/diffusers/training/sdxl)
- [ ] kandinsky.md[Kandinsky 2.2](https://huggingface.co/docs/diffusers/training/kandinsky)
- [ ] wuerstchen[Wuerstchen](https://huggingface.co/docs/diffusers/training/wuerstchen)
- [ ] controlnet.md[ControlNet](https://huggingface.co/docs/diffusers/training/controlnet)
- [ ] t2i_adapters.md[T2I-Adapters](https://huggingface.co/docs/diffusers/training/t2i_adapters)
- [ ] instructpix2pix.md[InstructPix2Pix](https://huggingface.co/docs/diffusers/training/instructpix2pix)

## METHODS
- [ ] text_inversion.md[Textual Inversion](https://huggingface.co/docs/diffusers/training/text_inversion)
- [ ] dreambooth.md[DreamBooth](https://huggingface.co/docs/diffusers/training/dreambooth)
- [ ] lora.md[LoRA](https://huggingface.co/docs/diffusers/training/lora)
- [ ] custom_diffusion.md[Custom Diffusion](https://huggingface.co/docs/diffusers/training/custom_diffusion)
- [ ] lcm_distill.md[Latent Consistency Distillation](https://huggingface.co/docs/diffusers/training/lcm_distill)
- [ ] ddpo.md[Reinforcement learning training with DDPO](https://huggingface.co/docs/diffusers/training/ddpo)

## TAKING DIFFUSERS BEYOND IMAGES
- [ ] using-diffusers/other-modalities.md [Other Modalities](https://huggingface.co/docs/diffusers/using-diffusers/other-modalities)

# OPTIMIZATION section
- [ ] opt_overview.md[Overview](https://huggingface.co/docs/diffusers/optimization/opt_overview)

## GENERAL OPTIMIZATIONS
- [ ] fp16.md[Speed up inference](https://huggingface.co/docs/diffusers/optimization/fp16)
- [ ] memory.md[Reduce memory usage](https://huggingface.co/docs/diffusers/optimization/memory)
- [ ] torch2.0.md[PyTorch 2.0](https://huggingface.co/docs/diffusers/optimization/torch2.0)
- [ ] xformers.md[xFormers](https://huggingface.co/docs/diffusers/optimization/xformers)
- [ ] tome.md[Token merging](https://huggingface.co/docs/diffusers/optimization/tome)

## OPTIMIZED MODEL TYPES
- [ ] stable_diffusion_jax_how_to.md [JAX/Flax](https://huggingface.co/docs/diffusers/using-diffusers/stable_diffusion_jax_how_to)
- [ ] onnx.md[ONNX](https://huggingface.co/docs/diffusers/optimization/onnx)
- [ ] open_vino.md[OpenVINO](https://huggingface.co/docs/diffusers/optimization/open_vino)
- [ ] coreml.md[Core ML](https://huggingface.co/docs/diffusers/optimization/coreml)

## OPTIMIZED HARDWARE
- [ ] mps.md[Metal Performance Shaders (MPS)](https://huggingface.co/docs/diffusers/optimization/mps)
- [ ] habana.md[Habana Gaudi](https://huggingface.co/docs/diffusers/optimization/habana)

## CONCEPTUAL GUIDES
- [ ] conceptual/philosophy.md[Philosophy](https://huggingface.co/docs/diffusers/conceptual/philosophy)
- [ ] using-diffusers/controlling_generation.md[Controlled generation](https://huggingface.co/docs/diffusers/using-diffusers/controlling_generation)
- [ ] conceptual/contribution.md[How to contribute?](https://huggingface.co/docs/diffusers/conceptual/contribution)
- [ ] conceptual/ethical_guidelines.md[Diffusers' Ethical Guidelines](https://huggingface.co/docs/diffusers/conceptual/ethical_guidelines)
- [ ] conceptual/evaluation.md[Evaluating Diffusion Models](https://huggingface.co/docs/diffusers/conceptual/evaluation)