diff --git a/docs/ecosystem/huggingface.md b/docs/ecosystem/huggingface.md
index 1595c21fb5..c12840144e 100644
--- a/docs/ecosystem/huggingface.md
+++ b/docs/ecosystem/huggingface.md
@@ -1,15 +1,16 @@
 # Hugging Face
 
-This page covers how to use the Hugging Face ecosystem (including the Hugging Face Hub) within LangChain.
+This page covers how to use the Hugging Face ecosystem (including the [Hugging Face Hub](https://huggingface.co)) within LangChain.
 It is broken into two parts: installation and setup, and then references to specific Hugging Face wrappers.
 
 ## Installation and Setup
 
 If you want to work with the Hugging Face Hub:
-- Install the Python SDK with `pip install huggingface_hub`
-- Get an OpenAI api key and set it as an environment variable (`HUGGINGFACEHUB_API_TOKEN`)
+- Install the Hub client library with `pip install huggingface_hub`
+- Create a Hugging Face account (it's free!)
+- Create an [access token](https://huggingface.co/docs/hub/security-tokens) and set it as an environment variable (`HUGGINGFACEHUB_API_TOKEN`)
 
-If you want work with Hugging Face python libraries:
+If you want work with the Hugging Face Python libraries:
 - Install `pip install transformers` for working with models and tokenizers
 - Install `pip install datasets` for working with datasets
 
@@ -18,7 +19,7 @@ If you want work with Hugging Face python libraries:
 ### LLM
 
 There exists two Hugging Face LLM wrappers, one for a local pipeline and one for a model hosted on Hugging Face Hub.
-Note that these wrappers only work for the following tasks: `text2text-generation`, `text-generation`
+Note that these wrappers only work for models that support the following tasks: [`text2text-generation`](https://huggingface.co/models?library=transformers&pipeline_tag=text2text-generation&sort=downloads), [`text-generation`](https://huggingface.co/models?library=transformers&pipeline_tag=text-classification&sort=downloads)
 
 To use the local pipeline wrapper:
 ```python
@@ -35,7 +36,7 @@ For a more detailed walkthrough of the Hugging Face Hub wrapper, see [this noteb
 ### Embeddings
 
 There exists two Hugging Face Embeddings wrappers, one for a local model and one for a model hosted on Hugging Face Hub.
-Note that these wrappers only work for `sentence-transformers` models.
+Note that these wrappers only work for [`sentence-transformers` models](https://huggingface.co/models?library=sentence-transformers&sort=downloads).
 
 To use the local pipeline wrapper:
 ```python
@@ -63,6 +64,6 @@ For a more detailed walkthrough of this, see [this notebook](../modules/utils/co
 
 ### Datasets
 
-Hugging Face has lots of great datasets that can be used to evaluate your LLM chains.
+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](../use_cases/evaluation/huggingface_datasets.ipynb)