diff --git a/docs/docs/integrations/providers/huggingface.mdx b/docs/docs/integrations/providers/huggingface.mdx
index a752a1b577..27fe4d42db 100644
--- a/docs/docs/integrations/providers/huggingface.mdx
+++ b/docs/docs/integrations/providers/huggingface.mdx
@@ -47,7 +47,7 @@ To use a the wrapper for a model hosted on Hugging Face Hub:
 ```python
 from langchain.embeddings import HuggingFaceHubEmbeddings
 ```
-For a more detailed walkthrough of this, see [this notebook](/docs/integrations/text_embedding/huggingfacehub.html)
+For a more detailed walkthrough of this, see [this notebook](/docs/integrations/text_embedding/huggingfacehub)
 
 ### Tokenizer
 
@@ -59,11 +59,11 @@ You can also use it to count tokens when splitting documents with
 from langchain.text_splitter import CharacterTextSplitter
 CharacterTextSplitter.from_huggingface_tokenizer(...)
 ```
-For a more detailed walkthrough of this, see [this notebook](/docs/modules/data_connection/document_transformers/text_splitters/huggingface_length_function.html)
+For a more detailed walkthrough of this, see [this notebook](/docs/modules/data_connection/document_transformers/text_splitters/huggingface_length_function)
 
 
 ### Datasets
 
 The Hugging Face Hub has lots of great [datasets](https://huggingface.co/datasets) that can be used to evaluate your LLM chains.
 
-For a detailed walkthrough of how to use them to do so, see [this notebook](/docs/use_cases/evaluation/huggingface_datasets.html)
+For a detailed walkthrough of how to use them to do so, see [this notebook](/docs/integrations/document_loaders/hugging_face_dataset)