diff --git a/docs/source/en/model_doc/layoutlmv3.mdx b/docs/source/en/model_doc/layoutlmv3.mdx
index 8463dbce7a0d50..8f115cf96ea56e 100644
--- a/docs/source/en/model_doc/layoutlmv3.mdx
+++ b/docs/source/en/model_doc/layoutlmv3.mdx
@@ -28,8 +28,9 @@ Tips:
     - images need to be resized and normalized with channels in regular RGB format. LayoutLMv2 on the other hand normalizes the images internally and expects the channels in BGR format.
     - text is tokenized using byte-pair encoding (BPE), as opposed to WordPiece. 
   Due to these differences in data preprocessing, one can use [`LayoutLMv3Processor`] which internally combines a [`LayoutLMv3FeatureExtractor`] (for the image modality) and a [`LayoutLMv3Tokenizer`]/[`LayoutLMv3TokenizerFast`] (for the text modality) to prepare all data for the model.
-- Regarding usage of [`LayoutLMv3Processor`], we refer to the [usage guide](layoutlmv2#usage-LayoutLMv2Processor) of its predecessor. 
+- Regarding usage of [`LayoutLMv3Processor`], we refer to the [usage guide](layoutlmv2#usage-layoutlmv2processor) of its predecessor. 
 - Demo notebooks for LayoutLMv3 can be found [here](https://github.com/NielsRogge/Transformers-Tutorials/tree/master/LayoutLMv3).
+- Demo scripts can be found [here](https://github.com/huggingface/transformers/tree/main/examples/research_projects/layoutlmv3).
 
 <img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/layoutlmv3_architecture.png"
 alt="drawing" width="600"/>