Add clip resources to the transformers documentation (#20190)

* WIP: Added CLIP resources from HuggingFace blog

* ADD: Notebooks documentation to clip

* Add link straight to notebook
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Change notebook links to colab
Co-authored-by: Ambuj Pawar <your_email@abc.example>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

docs/source/en/model_doc/clip.mdx

@@ -75,6 +75,25 @@ encode the text and prepare the images. The following example shows how to get t
 
 This model was contributed by [valhalla](https://huggingface.co/valhalla). The original code can be found [here](https://github.com/openai/CLIP).
 
+## Resources
+
+A list of official Hugging Face and community (indicated by 🌎) resources to help you get started with CLIP. If you're
+interested in submitting a resource to be included here, please feel free to open a Pull Request and we will review it.
+The resource should ideally demonstrate something new instead of duplicating an existing resource.
+
+<PipelineTag pipeline="text-to-image"/>
+- A blog post on [How to use CLIP to retrieve images from text](https://huggingface.co/blog/fine-tune-clip-rsicd).
+- A blog bost on [How to use CLIP for Japanese text to image generation](https://huggingface.co/blog/japanese-stable-diffusion).
+
+
+<PipelineTag pipeline="image-to-text"/>
+- A notebook showing [Video to text matching with CLIP for videos](https://colab.research.google.com/github/NielsRogge/Transformers-Tutorials/blob/master/X-CLIP/Video_text_matching_with_X_CLIP.ipynb).
+
+
+<PipelineTag pipeline="zero-shot-classification"/>
+- A notebook showing [Zero shot video classification using CLIP for video](https://colab.research.google.com/github/NielsRogge/Transformers-Tutorials/blob/master/X-CLIP/Zero_shot_classify_a_YouTube_video_with_X_CLIP.ipynb).
+
+
 ## CLIPConfig
 
 [[autodoc]] CLIPConfig