From 9fd337e098d16548ad0dfab9fefe6ee9cbed399a Mon Sep 17 00:00:00 2001
From: osrm <90407222+osrm@users.noreply.github.com>
Date: Tue, 6 May 2025 14:30:34 +0900
Subject: [PATCH 1/4] fix invalid link lora.md
---
docs/source/en/training/lora.md | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/docs/source/en/training/lora.md b/docs/source/en/training/lora.md
index c1f81c48b848..72378794364d 100644
--- a/docs/source/en/training/lora.md
+++ b/docs/source/en/training/lora.md
@@ -87,7 +87,7 @@ Lastly, if you want to train a model on your own dataset, take a look at the [Cr
-The following sections highlight parts of the training script that are important for understanding how to modify it, but it doesn't cover every aspect of the script in detail. If you're interested in learning more, feel free to read through the [script](https://github.com/huggingface/diffusers/blob/main/examples/text_to_image/text_to_image_lora.py) and let us know if you have any questions or concerns.
+The following sections highlight parts of the training script that are important for understanding how to modify it, but it doesn't cover every aspect of the script in detail. If you're interested in learning more, feel free to read through the [script](https://github.com/huggingface/diffusers/blob/main/examples/text_to_image/train_text_to_image_lora.py) and let us know if you have any questions or concerns.
From 2b85fe16967a4b51d1b5568ab86a421e994637f8 Mon Sep 17 00:00:00 2001
From: osrm <90407222+osrm@users.noreply.github.com>
Date: Tue, 6 May 2025 14:43:58 +0900
Subject: [PATCH 2/4] fix invalid link controlnet_sdxl.md
The Hugging Face models page now uses the tags parameter instead of the other parameter for tag-based filtering. Therefore, to simultaneously apply both the "Stable Diffusion XL" and "ControlNet" tags, the following URL should be used: https://huggingface.co/models?tags=stable-diffusion-xl,controlnet
---
docs/source/en/api/pipelines/controlnet_sdxl.md | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/docs/source/en/api/pipelines/controlnet_sdxl.md b/docs/source/en/api/pipelines/controlnet_sdxl.md
index f299702297b4..399d8891b62a 100644
--- a/docs/source/en/api/pipelines/controlnet_sdxl.md
+++ b/docs/source/en/api/pipelines/controlnet_sdxl.md
@@ -24,7 +24,7 @@ The abstract from the paper is:
*We present ControlNet, a neural network architecture to add spatial conditioning controls to large, pretrained text-to-image diffusion models. ControlNet locks the production-ready large diffusion models, and reuses their deep and robust encoding layers pretrained with billions of images as a strong backbone to learn a diverse set of conditional controls. The neural architecture is connected with "zero convolutions" (zero-initialized convolution layers) that progressively grow the parameters from zero and ensure that no harmful noise could affect the finetuning. We test various conditioning controls, eg, edges, depth, segmentation, human pose, etc, with Stable Diffusion, using single or multiple conditions, with or without prompts. We show that the training of ControlNets is robust with small (<50k) and large (>1m) datasets. Extensive results show that ControlNet may facilitate wider applications to control image diffusion models.*
-You can find additional smaller Stable Diffusion XL (SDXL) ControlNet checkpoints from the 🤗 [Diffusers](https://huggingface.co/diffusers) Hub organization, and browse [community-trained](https://huggingface.co/models?other=stable-diffusion-xl&other=controlnet) checkpoints on the Hub.
+You can find additional smaller Stable Diffusion XL (SDXL) ControlNet checkpoints from the 🤗 [Diffusers](https://huggingface.co/diffusers) Hub organization, and browse [community-trained](https://huggingface.co/models?tags=stable-diffusion-xl,controlnet) checkpoints on the Hub.
From fdb952c410e85255fae75128811bb95ed58b275b Mon Sep 17 00:00:00 2001
From: osrm <90407222+osrm@users.noreply.github.com>
Date: Tue, 6 May 2025 14:49:22 +0900
Subject: [PATCH 3/4] fix invalid link cosine_dpm.md
"https://github.com/Stability-AI/stable-audio-tool" -> "https://github.com/Stability-AI/stable-audio-tools"
---
docs/source/en/api/schedulers/cosine_dpm.md | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/docs/source/en/api/schedulers/cosine_dpm.md b/docs/source/en/api/schedulers/cosine_dpm.md
index 7685269c2145..e627ac3e2e83 100644
--- a/docs/source/en/api/schedulers/cosine_dpm.md
+++ b/docs/source/en/api/schedulers/cosine_dpm.md
@@ -13,7 +13,7 @@ specific language governing permissions and limitations under the License.
# CosineDPMSolverMultistepScheduler
The [`CosineDPMSolverMultistepScheduler`] is a variant of [`DPMSolverMultistepScheduler`] with cosine schedule, proposed by Nichol and Dhariwal (2021).
-It is being used in the [Stable Audio Open](https://arxiv.org/abs/2407.14358) paper and the [Stability-AI/stable-audio-tool](https://github.com/Stability-AI/stable-audio-tool) codebase.
+It is being used in the [Stable Audio Open](https://arxiv.org/abs/2407.14358) paper and the [Stability-AI/stable-audio-tool](https://github.com/Stability-AI/stable-audio-tools) codebase.
This scheduler was contributed by [Yoach Lacombe](https://huggingface.co/ylacombe).
From 1d88f441e8bfca17b56e672b8253d9d0dc689537 Mon Sep 17 00:00:00 2001
From: osrm <90407222+osrm@users.noreply.github.com>
Date: Tue, 6 May 2025 20:02:47 +0900
Subject: [PATCH 4/4] Update controlnet_sdxl.md
---
docs/source/en/api/pipelines/controlnet_sdxl.md | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/docs/source/en/api/pipelines/controlnet_sdxl.md b/docs/source/en/api/pipelines/controlnet_sdxl.md
index 399d8891b62a..f299702297b4 100644
--- a/docs/source/en/api/pipelines/controlnet_sdxl.md
+++ b/docs/source/en/api/pipelines/controlnet_sdxl.md
@@ -24,7 +24,7 @@ The abstract from the paper is:
*We present ControlNet, a neural network architecture to add spatial conditioning controls to large, pretrained text-to-image diffusion models. ControlNet locks the production-ready large diffusion models, and reuses their deep and robust encoding layers pretrained with billions of images as a strong backbone to learn a diverse set of conditional controls. The neural architecture is connected with "zero convolutions" (zero-initialized convolution layers) that progressively grow the parameters from zero and ensure that no harmful noise could affect the finetuning. We test various conditioning controls, eg, edges, depth, segmentation, human pose, etc, with Stable Diffusion, using single or multiple conditions, with or without prompts. We show that the training of ControlNets is robust with small (<50k) and large (>1m) datasets. Extensive results show that ControlNet may facilitate wider applications to control image diffusion models.*
-You can find additional smaller Stable Diffusion XL (SDXL) ControlNet checkpoints from the 🤗 [Diffusers](https://huggingface.co/diffusers) Hub organization, and browse [community-trained](https://huggingface.co/models?tags=stable-diffusion-xl,controlnet) checkpoints on the Hub.
+You can find additional smaller Stable Diffusion XL (SDXL) ControlNet checkpoints from the 🤗 [Diffusers](https://huggingface.co/diffusers) Hub organization, and browse [community-trained](https://huggingface.co/models?other=stable-diffusion-xl&other=controlnet) checkpoints on the Hub.