diff --git a/docs/docs/Components/components-embedding-models.md b/docs/docs/Components/components-embedding-models.md
index 5f6bfb2a8..5dfa36d18 100644
--- a/docs/docs/Components/components-embedding-models.md
+++ b/docs/docs/Components/components-embedding-models.md
@@ -179,7 +179,7 @@ This component connects to Google's generative AI embedding service using the Go
 
 :::note
 This component is deprecated as of Langflow version 1.0.18.
-Instead, use the [Hugging Face API Embeddings component](#hugging-face-embeddings-inference-api).
+Instead, use the [Hugging Face Embeddings Inference component](#hugging-face-embeddings-inference).
 :::
 
 This component loads embedding models from HuggingFace.
@@ -202,29 +202,42 @@ Use this component to generate embeddings using locally downloaded Hugging Face
 |------|--------------|------|
 | embeddings | Embeddings | The generated embeddings |
 
-## Hugging Face embeddings Inference API
+## Hugging Face embeddings inference
 
-This component generates embeddings using [Hugging Face Inference API models](https://huggingface.co/).
+This component generates embeddings using [Hugging Face Inference API models](https://huggingface.co/) and requires a [Hugging Face API token](https://huggingface.co/docs/hub/security-tokens) to authenticate. Local inference models do not require an API key.
 
-Use this component to create embeddings with Hugging Face's hosted models.
+Use this component to create embeddings with Hugging Face's hosted models, or to connect to your own locally hosted models.
 
 ### Inputs
 
 | Name | Display Name | Info |
 |------|--------------|------|
-| API Key | API Key | API key for accessing the Hugging Face Inference API |
-| API URL | API URL | URL of the Hugging Face Inference API |
-| Model Name | Model Name | Name of the model to use for embeddings |
-| Cache Folder | Cache Folder | Folder path to cache Hugging Face models |
-| Encode Kwargs | Encoding Arguments | Additional arguments for the encoding process |
-| Model Kwargs | Model Arguments | Additional arguments for the model |
-| Multi Process | Multi-Process | Whether to use multiple processes |
+| API Key | API Key | The API key for accessing the Hugging Face Inference API. |
+| API URL | API URL | The URL of the Hugging Face Inference API. |
+| Model Name | Model Name | The name of the model to use for embeddings. |
+| Cache Folder | Cache Folder | The folder path to cache Hugging Face models. |
+| Encode Kwargs | Encoding Arguments | Additional arguments for the encoding process. |
+| Model Kwargs | Model Arguments | Additional arguments for the model. |
+| Multi Process | Multi-Process | Whether to use multiple processes. |
 
 ### Outputs
 
 | Name | Display Name | Info |
 |------|--------------|------|
-| embeddings | Embeddings | The generated embeddings |
+| embeddings | Embeddings | The generated embeddings. |
+
+### Connect the Hugging Face component to a local embeddings model
+
+To run an embeddings inference locally, see the [HuggingFace documentation](https://huggingface.co/docs/text-embeddings-inference/local_cpu).
+
+To connect the local Hugging Face model to the **Hugging Face embeddings inference** component and use it in a flow, follow these steps:
+
+1. Create a [Vector store RAG flow](/starter-projects-vector-store-rag).
+There are two embeddings models in this flow that you can replace with **Hugging Face** embeddings inference components.
+2. Replace both **OpenAI** embeddings model components with **Hugging Face** model components.
+3. Connect both **Hugging Face** components to the **Embeddings** ports of the **Astra DB vector store** components.
+4. In the **Hugging Face** components, set the **Inference Endpoint** field to the URL of your local inference model. **The **API Key** field is not required for local inference.**
+5. Run the flow. The local inference models generate embeddings for the input text.
 
 ## LM Studio Embeddings
 
diff --git a/docs/docs/Components/components-models.md b/docs/docs/Components/components-models.md
index f1943ded4..f2f30e772 100644
--- a/docs/docs/Components/components-models.md
+++ b/docs/docs/Components/components-models.md
@@ -211,19 +211,41 @@ For more information, see the [Groq documentation](https://groq.com/).
 
 ## Hugging Face API
 
-This component generates text using Hugging Face's language models.
+This component sends requests to the Hugging Face API to generate text using the model specified in the **Model ID** field.
+
+The Hugging Face API is a hosted inference API for models hosted on Hugging Face, and requires a [Hugging Face API token](https://huggingface.co/docs/hub/security-tokens) to authenticate.
+
+In this example based on the [Basic prompting flow](/starter-projects-basic-prompting), the **Hugging Face API** model component replaces the **Open AI** model. By selecting different hosted models, you can see how different models return different results.
+
+1. Create a [Basic prompting flow](/starter-projects-basic-prompting).
+
+2. Replace the **OpenAI** model component with a **Hugging Face API** model component.
+
+3. In the **Hugging Face API** component, add your Hugging Face API token to the **API Token** field.
+
+4. Open the **Playground** and ask a question to the model, and see how it responds.
+
+5. Try different models, and see how they perform differently.
 
 For more information, see the [Hugging Face documentation](https://huggingface.co/).
 
 ### Inputs
 
-| Name                | Display Name     | Info                                      |
-|---------------------|-------------------|-------------------------------------------|
-| Endpoint URL        | Endpoint URL      | The URL of the Hugging Face Inference API endpoint. |
-| Task                | Task              | Specifies the task for text generation.   |
-| API Token           | API Token         | The API token required for authentication.|
-| Model Kwargs        | Model Kwargs      | Additional keyword arguments for the model.|
-| Input Value         | Input Value       | The input text for text generation.       |
+| Name           | Type          | Description                                                     |
+|----------------|---------------|-----------------------------------------------------------------|
+| model_id       | String        | The model ID from Hugging Face Hub. For example, "gpt2", "facebook/bart-large". |
+| huggingfacehub_api_token | SecretString | Your Hugging Face API token for authentication.       |
+| temperature    | Float         | Controls randomness in the output. Range: [0.0, 1.0]. Default: 0.7. |
+| max_new_tokens | Integer       | Maximum number of tokens to generate. Default: 512.             |
+| top_p          | Float         | Nucleus sampling parameter. Range: [0.0, 1.0]. Default: 0.95.   |
+| top_k          | Integer       | Top-k sampling parameter. Default: 50.                          |
+| model_kwargs   | Dictionary    | Additional keyword arguments to pass to the model.              |
+
+### Outputs
+
+| Name  | Type          | Description                                                      |
+|-------|---------------|------------------------------------------------------------------|
+| model | LanguageModel | An instance of HuggingFaceHub configured with the specified parameters. |
 
 ## LMStudio