From 9360bb94c39a20f3b9e555476261d96c219c0090 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?M=2E=20Tolga=20Cang=C3=B6z?= <46008593+standardAI@users.noreply.github.com> Date: Fri, 10 Mar 2023 16:17:10 +0300 Subject: [PATCH] Update quicktour.mdx (#2637) Fix typo --- docs/source/en/quicktour.mdx | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/source/en/quicktour.mdx b/docs/source/en/quicktour.mdx index 27db009c..3aecb422 100644 --- a/docs/source/en/quicktour.mdx +++ b/docs/source/en/quicktour.mdx @@ -205,7 +205,7 @@ Schedulers manage going from a noisy sample to a less noisy sample given the mod -🧨 Diffusers is a toolbox for building diffusion systems. While the [`DiffusionPipeline`] is a convenient way to get started with a pre-built diffusion system, you can also choose your own the model and scheduler components separately to build a custom diffusion system. +🧨 Diffusers is a toolbox for building diffusion systems. While the [`DiffusionPipeline`] is a convenient way to get started with a pre-built diffusion system, you can also choose your own model and scheduler components separately to build a custom diffusion system. @@ -310,4 +310,4 @@ Hopefully you generated some cool images with 🧨 Diffusers in this quicktour! * See example official and community [training or finetuning scripts](https://github.com/huggingface/diffusers/tree/main/examples#-diffusers-examples) for a variety of use cases. * Learn more about loading, accessing, changing and comparing schedulers in the [Using different Schedulers](./using-diffusers/schedulers) guide. * Explore prompt engineering, speed and memory optimizations, and tips and tricks for generating higher quality images with the [Stable Diffusion](./stable_diffusion) guide. -* Dive deeper into speeding up 🧨 Diffusers with guides on [optimized PyTorch on a GPU](./optimization/fp16), and inference guides for running [Stable Diffusion on Apple Silicon (M1/M2)](./optimization/mps) and [ONNX Runtime](./optimization/onnx). \ No newline at end of file +* Dive deeper into speeding up 🧨 Diffusers with guides on [optimized PyTorch on a GPU](./optimization/fp16), and inference guides for running [Stable Diffusion on Apple Silicon (M1/M2)](./optimization/mps) and [ONNX Runtime](./optimization/onnx).