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[docs] update the broken links (#3568)

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update the broken links

update the broken links for training folder doc
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Brandon
2023-05-27 03:10:32 +08:00
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@@ -407,9 +407,9 @@ Once training is complete, take a look at the final 🦋 images 🦋 generated b
## Next steps
Unconditional image generation is one example of a task that can be trained. You can explore other tasks and training techniques by visiting the [🧨 Diffusers Training Examples](./training/overview) page. Here are some examples of what you can learn:
Unconditional image generation is one example of a task that can be trained. You can explore other tasks and training techniques by visiting the [🧨 Diffusers Training Examples](../training/overview) page. Here are some examples of what you can learn:
* [Textual Inversion](./training/text_inversion), an algorithm that teaches a model a specific visual concept and integrates it into the generated image.
* [DreamBooth](./training/dreambooth), a technique for generating personalized images of a subject given several input images of the subject.
* [Guide](./training/text2image) to finetuning a Stable Diffusion model on your own dataset.
* [Guide](./training/lora) to using LoRA, a memory-efficient technique for finetuning really large models faster.
* [Textual Inversion](../training/text_inversion), an algorithm that teaches a model a specific visual concept and integrates it into the generated image.
* [DreamBooth](../training/dreambooth), a technique for generating personalized images of a subject given several input images of the subject.
* [Guide](../training/text2image) to finetuning a Stable Diffusion model on your own dataset.
* [Guide](../training/lora) to using LoRA, a memory-efficient technique for finetuning really large models faster.