diff --git a/docs/docs/Integrations/Nvidia/integrations-nvidia-nim-wsl2.md b/docs/docs/Integrations/Nvidia/integrations-nvidia-nim-wsl2.md
index a2c8c9c54..0d0d1642b 100644
--- a/docs/docs/Integrations/Nvidia/integrations-nvidia-nim-wsl2.md
+++ b/docs/docs/Integrations/Nvidia/integrations-nvidia-nim-wsl2.md
@@ -5,18 +5,17 @@ slug: /integrations-nvidia-ingest-wsl2
 
 Connect **Langflow** with **NVIDIA NIM** on an RTX Windows system with [Windows Subsystem for Linux 2 (WSL2)](https://learn.microsoft.com/en-us/windows/wsl/install) installed.
 
-[NVIDIA NIM](https://docs.nvidia.com/nim/index.html) provides containers to self-host GPU-accelerated inferencing microservices.
-This example deploys the `mistral-nemo-12b-instruct` NIM on an **RTX Windows system** with **WSL2** and uses it as a model component in **Langflow**.
+[NVIDIA NIM (NVIDIA Inference Microservices)](https://docs.nvidia.com/nim/index.html) provides containers to self-host GPU-accelerated inferencing microservices.
+In this example, you connect a model component in **Langflow** to a deployed `mistral-nemo-12b-instruct` NIM on an **RTX Windows system** with **WSL2**.
 
 For more information on NVIDIA NIM, see the [NVIDIA documentation](https://docs.nvidia.com/nim/index.html).
 
 ## Prerequisites
 
 * [NVIDIA NIM WSL2 installed](https://docs.nvidia.com/nim/wsl2/latest/getting-started.html)
-* A NIM container deployed. The prerequisites vary between models.
+* A NIM container deployed according to the model's instructions. Prerequisites vary between models.
 For example, to deploy the `mistral-nemo-12b-instruct` NIM, follow the instructions for **Windows on RTX AI PCs (Beta)** on your [model's deployment overview](https://build.nvidia.com/nv-mistralai/mistral-nemo-12b-instruct/deploy?environment=wsl2.md)
-* [WSL2 installed](https://learn.microsoft.com/en-us/windows/wsl/install)
-* Windows 11 build 23H2 (and later)
+* Windows 11 build 23H2 or later
 * At least 12 GB of RAM
 
 ## Use the NVIDIA NIM in a flow
@@ -25,9 +24,7 @@ To connect the NIM you've deployed with Langflow, add the **NVIDIA** model compo
 
 1. Create a [basic prompting flow](/get-started-quickstart).
 2. Replace the **OpenAI** model component with the **NVIDIA** component.
-3. In the **NVIDIA** component's **Base URL** field, add the URL your NIM is accessible at. If you followed your model's [deployment instructions](https://build.nvidia.com/nv-mistralai/mistral-nemo-12b-instruct/deploy?environment=wsl2.md), the value is `http://0.0.0.0:8000/v1`.
+3. In the **NVIDIA** component's **Base URL** field, add the URL where your NIM is accessible. If you followed your model's [deployment instructions](https://build.nvidia.com/nv-mistralai/mistral-nemo-12b-instruct/deploy?environment=wsl2.md), the value is `http://0.0.0.0:8000/v1`.
 4. In the **NVIDIA** component's **NVIDIA API Key** field, add your NVIDIA API Key.
 5. Select your model from the **Model Name** dropdown.
-6. Open the **Playground** and chat with your **NIM** model.
-
-
+6. Open the **Playground** and chat with your **NIM** model.
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