Merge branch 'latest' into yt/add-gpu-to-statuses

.ci/patch_notebooks.py

@@ -93,7 +93,7 @@ def has_additional_deps(str_part):
                                 break
                             # keep indention
                             updated_line = " " + updated_line
-                    updated_lines.append(updated_line + "# " + line)
+                    updated_lines.append(updated_line + "\n# " + line)
             else:
                 updated_lines.append(line)
         else:

notebooks/stable-video-diffusion/README.md

@@ -1,7 +1,7 @@
 # Image to Video Generation with Stable Video Diffusion
 
 [Stable Video Diffusion (SVD)](https://stability.ai/stable-video) Image-to-Video is a diffusion model that takes in a still image as a conditioning frame, and generates a video from it. In this tutorial we consider how to convert and run Stable Video Diffusion using OpenVINO.
-We will use [stable-video-diffusion-img2video-xt](https://huggingface.co/stabilityai/stable-video-diffusion-img2vid-xt) model as example. Additionally, to speedup video generation process we apply [AnimateLCM](https://arxiv.org/abs/2402.00769) LoRA weights.
+We will use [stable-video-diffusion-img2video-xt](https://huggingface.co/stabilityai/stable-video-diffusion-img2vid-xt) model as example. Additionally, to speedup video generation process we apply [AnimateLCM](https://arxiv.org/abs/2402.00769) LoRA weights and run optimization with [NNCF](https://github.com/openvinotoolkit/nncf/).
 
 ![result](https://github.com/openvinotoolkit/openvino_notebooks/assets/29454499/ae8a77b2-b5c9-45c5-a103-6e46c686739f)
 
@@ -17,6 +17,8 @@ Notebook contains the following steps:
   - Convert U-Net
   - Convert VAE Encoder and Decoder
 - Create Stable Video Diffusion Pipeline with OpenVINO
+- Optimize pipeline with [NNCF](https://github.com/openvinotoolkit/nncf/)
+- Compare results of original and optimized pipelines
 - Interactive Demo
 
 ## Installation Instructions