all models are now prepended with the provider name (#57089)

content/github-models/github-models-at-scale/use-models-at-scale.md

@@ -33,6 +33,8 @@ See [AUTOTITLE](/github-models/about-github-models).
 
 ## Best practices for using {% data variables.product.prodname_github_models %} at scale
 
+The following best practices can help you effectively use {% data variables.product.prodname_github_models %} across your organization.
+
 ### Compare and evaluate AI models for governance and compliance
 
 Review and compare available AI models against your company’s governance, data security, and compliance requirements. You can do this in any Models-enabled {% data variables.product.github %} repository or in the {% data variables.product.prodname_github_models %} catalog from the {% data variables.product.prodname_marketplace %} at https://github.com/marketplace?type=models. Your considerations may include:
@@ -113,7 +115,7 @@ Large software development projects often contain issues full of technical detai
          important questions.
      - role: user
        content: 'Summarize this issue, please - {% raw %}{{input}}{% endraw %}'
-   model: gpt-4o
+   model: openai/gpt-4o
    modelParameters:
      max_tokens: 4096
    ```

content/github-models/quickstart.md

@@ -22,7 +22,6 @@ This guide helps you try out models quickly in the playground, then shows you ho
 ## Step 1: Try models in the playground
 
 1. Go to **[https://github.com/marketplace/models](https://github.com/marketplace/models)**.
-
 1. In the playground, select at least one model from the dropdown menu.
 1. Test out different prompts using the **Chat** view, and compare responses from different models.
 1. Use the **Parameters** view to customize the parameters for the models you are testing, then see how they impact responses.
@@ -70,10 +69,9 @@ To call models programmatically, you’ll need:
 
 1. To try other models, change the value of the `model` field in the JSON payload to one from the [marketplace](https://github.com/marketplace/models).
 
-## Step 3: Run models in GitHub Actions
+## Step 3: Run models in {% data variables.product.prodname_actions %}
 
 1. In your repository, create a workflow file at `.github/workflows/models-demo.yml`.
-
 1. Paste the following workflow into the file you just created.
 
     ```yaml copy
@@ -118,13 +116,12 @@ This example shows how to send a prompt to a model and use the response in your
 {% data variables.product.prodname_github_models %} supports reusable prompts defined in `.prompt.yml` files. Once you add this file to your repository, it will appear in the Models page of your repository and can be run directly in the Prompt Editor and evaluation tooling. Learn more about [AUTOTITLE](/github-models/use-github-models/storing-prompts-in-github-repositories).
 
 1. In your repository, create a file named `summarize.prompt.yml`. You can save it in any directory.
-
 1. Paste the following example prompt into the file you just created.
 
     ```yaml copy
     name: Text Summarizer
     description: Summarizes input text concisely
-    model: gpt-4o-mini
+    model: openai/gpt-4o-mini
     modelParameters:
       temperature: 0.5
     messages:
@@ -139,11 +136,8 @@ This example shows how to send a prompt to a model and use the response in your
     ```
 
 1. Commit and push the file to your repository.
-
 1. Go to the **Models** tab in your repository.
-
 1. In the navigation menu, click **{% octicon "note" aria-hidden="true" aria-label="none" %} Prompts**, then click on the prompt file.
-
 1. The prompt will open in the prompt editor. Click **Run**. A right-hand sidebar will appear asking you to enter input text. Enter any input text, then click **Run** again in the bottom right corner to test it out.
 
    > [!NOTE]
@@ -154,13 +148,12 @@ This example shows how to send a prompt to a model and use the response in your
 Evaluations help you measure how different models respond to the same inputs so you can choose the best one for your use case.
 
 1. Go back to the `summarize.prompt.yml` file you created in the previous step.
-
 1. Update the file to match the following example.
 
    ```yaml copy
    name: Text Summarizer
    description: Summarizes input text concisely
-   model: gpt-4o-mini
+   model: openai/gpt-4o-mini
    modelParameters:
      temperature: 0.5
    messages:
@@ -190,11 +183,8 @@ Evaluations help you measure how different models respond to the same inputs so
    ```
 
 1. Commit and push the file to your repository.
-
 1. In your repository, click the **Models** tab. Then click **{% octicon "note" aria-hidden="true" aria-label="none" %} Prompts** and reopen the same prompt in the prompt editor.
-
 1. In the top left-hand corner, you can toggle the view from **Edit** to **Compare**. Click **Compare**.
-
 1. Your evaluation will be set up automatically. Click **Run** to see results.
 
    > [!TIP]

content/github-models/use-github-models/storing-prompts-in-github-repositories.md

@@ -8,11 +8,11 @@ versions:
   ghec: '*'
 ---
 
-Prompts can be stored as files directly within GitHub repositories. This unlocks the ability to view your prompts in an organized UI, share them with non-technical stakeholders, and run seamless iterations and comparisons on adjustments to models and prompts.
+Prompts can be stored as files directly within {% data variables.product.github %} repositories. This unlocks the ability to view your prompts in an organized UI, share them with non-technical stakeholders, and run seamless iterations and comparisons on adjustments to models and prompts.
 
 ## Benefits
 
-* Easy integration with the new suite of AI development tools directly on GitHub.
+* Easy integration with the new suite of AI development tools directly on {% data variables.product.github %}.
 * Simple and scalable from simple to complex use cases.
 * Uses a widely supported format, compatible with existing tools.
 
@@ -27,7 +27,7 @@ Example:
 ``` yaml copy
 name: Text Summarizer
 description: Summarizes input text concisely
-model: gpt-4o-mini
+model: openai/gpt-4o-mini
 modelParameters:
   temperature: 0.5
 messages: