fixed review2 feedback.

Author: samuel100

articles/ai-foundry-local/concepts/foundry-local-architecture.md

@@ -80,7 +80,7 @@ The model cache stores downloaded AI models locally on your device, which ensure
 Before models can be used with Foundry Local, they must be compiled and optimized in the [ONNX](https://onnx.ai) format. Microsoft provides a selection of published models in the Azure AI Foundry Model Catalog that are already optimized for Foundry Local. However, you aren't limited to those models - by using [Olive](https://microsoft.github.io/Olive/). Olive is a powerful framework for preparing AI models for efficient inference. It converts models into the ONNX format, optimizes their graph structure, and applies techniques like quantization to improve performance on local hardware.
 
 > [!TIP]
-> To learn more about compiling models for Foundry Local, read [How to compile Hugging Face models to run on Foundry Local](../how-to/how-to-compile-huggingface-models.md).
+> To learn more about compiling models for Foundry Local, read [How to compile Hugging Face models to run on Foundry Local](../how-to/how-to-compile-hugging-face-models.md).
 
 ### Hardware abstraction layer
 

articles/ai-foundry-local/get-started.md

@@ -93,5 +93,5 @@ foundry cache --help
 - [Explore the Foundry Local documentation](index.yml)
 - [Learn about best practices and troubleshooting](reference/reference-best-practice.md)
 - [Explore the Foundry Local API reference](reference/reference-catalog-api.md)
-- [Learn how to compile Hugging Face models](how-to/how-to-compile-huggingface-models.md)
+- [Learn how to compile Hugging Face models](how-to/how-to-compile-hugging-face-models.md)
 

articles/ai-foundry-local/how-to/how-to-compile-huggingface-models.md renamed to articles/ai-foundry-local/how-to/how-to-compile-hugging-face-models.md

@@ -1,7 +1,7 @@
 ---
-title: How to compile HuggingFace models to run on Foundry Local
+title: How to compile Hugging Face models to run on Foundry Local
 titleSuffix: Foundry Local
-description: Learn how to compile and run HuggingFace models with Foundry Local.
+description: Learn how to compile and run Hugging Face models with Foundry Local.
 manager: scottpolly
 ms.service: azure-ai-foundry
 ms.custom: build-2025
@@ -11,7 +11,7 @@ ms.author: samkemp
 author: samuel100
 ---
 
-# How to compile HuggingFace models to run on Foundry Local
+# How to compile Hugging Face models to run on Foundry Local
 
 Foundry Local runs ONNX models on your device with high performance. While the model catalog offers _out-of-the-box_ precompiled options, you can use any model in the ONNX format.
 
@@ -21,7 +21,7 @@ This guide shows you how to:
 
 > [!div class="checklist"]
 >
-> - **Convert and optimize** models from HuggingFace to run in Foundry Local. You'll use the `Llama-3.2-1B-Instruct` model as an example, but you can use any generative AI model from HuggingFace.
+> - **Convert and optimize** models from Hugging Face to run in Foundry Local. You'll use the `Llama-3.2-1B-Instruct` model as an example, but you can use any generative AI model from Hugging Face.
 > - **Run** your optimized models with Foundry Local
 
 ## Prerequisites
@@ -49,9 +49,9 @@ pip install olive-ai[auto-opt]
 > [!TIP]
 > For best results, install Olive in a virtual environment using [venv](https://docs.python.org/3/library/venv.html) or [conda](https://www.anaconda.com/docs/getting-started/miniconda/main).
 
-## Sign in to HuggingFace
+## Sign in to Hugging Face
 
-You optimize the `Llama-3.2-1B-Instruct` model, which requires HuggingFace authentication:
+You optimize the `Llama-3.2-1B-Instruct` model, which requires Hugging Face authentication:
 
 ### [Bash](#tab/Bash)
 
@@ -68,7 +68,7 @@ huggingface-cli login
 ---
 
 > [!NOTE]
-> You must first [create a HuggingFace token](https://huggingface.co/docs/hub/security-tokens) and [request model access](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct) before proceeding.
+> You must first [create a Hugging Face token](https://huggingface.co/docs/hub/security-tokens) and [request model access](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct) before proceeding.
 
 ## Compile the model
 
@@ -113,15 +113,15 @@ The command uses the following parameters:
 
 | Parameter            | Description                                                                       |
 | -------------------- | --------------------------------------------------------------------------------- |
-| `model_name_or_path` | Model source: HuggingFace ID, local path, or Azure AI Model registry ID           |
+| `model_name_or_path` | Model source: Hugging Face ID, local path, or Azure AI Model registry ID           |
 | `output_path`        | Where to save the optimized model                                                 |
 | `device`             | Target hardware: `cpu`, `gpu`, or `npu`                                           |
 | `provider`           | Execution provider (for example, `CPUExecutionProvider`, `CUDAExecutionProvider`) |
 | `precision`          | Model precision: `fp16`, `fp32`, `int4`, or `int8`                                |
 | `use_ort_genai`      | Creates inference configuration files                                             |
 
 > [!TIP]
-> If you have a local copy of the model, you can use a local path instead of the HuggingFace ID. For example, `--model_name_or_path models/llama-3.2-1B-Instruct`. Olive handles the conversion, optimization, and quantization automatically.
+> If you have a local copy of the model, you can use a local path instead of the Hugging Face ID. For example, `--model_name_or_path models/llama-3.2-1B-Instruct`. Olive handles the conversion, optimization, and quantization automatically.
 
 ### Step 2: Rename the output model
 
@@ -159,10 +159,10 @@ Foundry Local requires a chat template JSON file called `inference_model.json` i
 }
 ```
 
-To create the chat template file, you can use the `apply_chat_template` method from the HuggingFace library:
+To create the chat template file, you can use the `apply_chat_template` method from the Hugging Face library:
 
 > [!NOTE]
-> The following example uses the Python HuggingFace library to create a chat template. The HuggingFace library is a dependency for Olive, so if you're using the same Python virtual environment you don't need to install. If you're using a different environment, install the library with `pip install transformers`.
+> The following example uses the Python Hugging Face library to create a chat template. The Hugging Face library is a dependency for Olive, so if you're using the same Python virtual environment you don't need to install. If you're using a different environment, install the library with `pip install transformers`.
 
 ```python
 # generate_inference_model.py

articles/ai-foundry-local/how-to/integrate-with-inference-sdks.md

@@ -48,5 +48,5 @@ When Foundry Local is running, it exposes an OpenAI-compatible REST API endpoint
 
 ## Next steps
 
-- [How to compile Hugging Face models to run on Foundry Local](how-to-compile-huggingface-models.md)
+- [How to compile Hugging Face models to run on Foundry Local](how-to-compile-hugging-face-models.md)
 - [Explore the Foundry Local CLI reference](../reference/reference-cli.md)

articles/ai-foundry-local/index.yml

@@ -44,7 +44,7 @@ landingContent:
           - text: Integrate with Inferencing SDKs
             url: how-to/integrate-with-inference-sdks.md
           - text: Compile Hugging Face models to run on Foundry Local
-            url: how-to/how-to-compile-huggingface-models.md
+            url: how-to/how-to-compile-hugging-face-models.md
   # Card
   - title: Reference
     linkLists:

articles/ai-foundry-local/reference/reference-catalog-api.md

@@ -1,4 +1,4 @@
----
+
 title: Catalog API Reference
 titleSuffix: Foundry Local
 description: Complete reference guide for the Foundry Local Model Catalog API.
@@ -9,7 +9,6 @@ ms.topic: reference
 ms.date: 05/02/2025
 ms.author: maanavdalal
 author: maanavd
----
 
 # Catalog API Reference
 
@@ -23,24 +22,19 @@ https://<catalog provider URI>/<provider subpath>
 
 Replace `<catalog provider URI>` and `<provider subpath>` with your specific catalog hosting information.
 
----
-
 ## Available APIs
 
 - **Get Model Details** - Retrieve information about a specific model
 - **Get Publisher Details** - Access publisher information
 - **List Publishers** - View all available publishers
 - **List Models** - Browse available models
 
----
-
 ## Authorization
 
 All endpoints must support:
 
 - Anonymous access (no authentication required)
 
----
 
 ## Get Model Details
 
@@ -60,7 +54,6 @@ GET https://<catalog provider URI>/<provider subpath>/models/{modelName}/version
 curl -X GET --location "https://<catalog provider URI>/<provider subpath>/models/Phi-3-mini-128k-instruct/version/12"
 ```
 
----
 
 ## Get Publisher Details
 
@@ -78,7 +71,6 @@ GET https://<catalog provider URI>/<provider subpath>/publishers/{publisherName}
 curl -X GET --location "https://<catalog provider URI>/<provider subpath>/publishers/contoso"
 ```
 
----
 
 ## List Publishers
 
@@ -98,7 +90,6 @@ curl -X POST --location "https://<catalog provider URI>/<provider subpath>/publi
   --data '{"continuationToken": ""}'
 ```
 
----
 
 ## List Models
 
@@ -145,7 +136,6 @@ curl -X POST --location "https://<catalog provider URI>/<provider subpath>/model
   }'
 ```
 
----
 
 ## Filterable Fields
 
@@ -183,6 +173,5 @@ You can order results by the following fields:
 - `displayName`
 - `publisher`
 
----
 
 For more information, refer to your catalog provider's API documentation.

articles/ai-foundry-local/toc.yml

@@ -16,7 +16,7 @@ items:
   - name: Integrate with Inferencing SDKs
     href: how-to/integrate-with-inference-sdks.md
   - name: Compile Hugging Face models to run on Foundry Local
-    href: how-to/how-to-compile-huggingface-models.md
+    href: how-to/how-to-compile-hugging-face-models.md
 - name: Tutorials
   expanded: true
   items:

articles/ai-foundry-local/tutorials/chat-application-with-open-web-ui.md

@@ -42,10 +42,10 @@ Before you start this tutorial, you need:
 
 4. **Connect Open Web UI to Foundry Local**:
 
-   1. Click **Settings** in the navigation menu
+   1. Select **Settings** in the navigation menu
    2. Select **Connections**
-   3. Click **Manage Direct Connections**
-   4. Click the **+** icon to add a connection
+   3. Select **Manage Direct Connections**
+   4. Select the **+** icon to add a connection
    5. Enter `http://localhost:5272/v1` for the URL
    6. Type any value (like `test`) for the API Key, since it cannot be empty
    7. Save your connection
@@ -60,4 +60,4 @@ That's it! You're now chatting with an AI model running entirely on your local d
 ## Next steps
 
 - [Build an application with LangChain](use-langchain-with-foundry-local.md)
-- [How to compile Hugging Face models to run on Foundry Local](../how-to/how-to-compile-huggingface-models.md)
+- [How to compile Hugging Face models to run on Foundry Local](../how-to/how-to-compile-hugging-face-models.md)

articles/ai-foundry-local/tutorials/use-langchain-with-foundry-local.md

@@ -82,4 +82,4 @@ print(ai_msg)
 ## Next steps
 
 - Explore the [LangChain documentation](https://python.langchain.com/docs/introduction) for more advanced features and capabilities.
-- [How to compile Hugging Face models to run on Foundry Local](../how-to/how-to-compile-huggingface-models.md)
+- [How to compile Hugging Face models to run on Foundry Local](../how-to/how-to-compile-hugging-face-models.md)

articles/ai-foundry-local/what-is-foundry-local.md

@@ -49,5 +49,5 @@ Install and run your first model by following the [Get started with Foundry Loca
 ## Next steps
 
 - [Get started with Foundry Local](get-started.md)
-- [How to compile Hugging Face models to run on Foundry Local](how-to/how-to-compile-huggingface-models.md)
+- [How to compile Hugging Face models to run on Foundry Local](how-to/how-to-compile-hugging-face-models.md)