README.md Dockersection formatting and wording fix

README.md

@@ -92,68 +92,64 @@ Don't forget to explore our sibling project, [Open WebUI Community](https://open
 > [!NOTE]  
 > Please note that for certain Docker environments, additional configurations might be needed. If you encounter any connection issues, our detailed guide on [Open WebUI Documentation](https://docs.openwebui.com/) is ready to assist you.
 
-### Quick Start with Docker 🐳
+### Quick Start with Docker (3 ways) 🐳
 
 > [!IMPORTANT]
 > When using Docker to install Open WebUI, make sure to include the `-v open-webui:/app/backend/data` in your Docker command. This step is crucial as it ensures your database is properly mounted and prevents any loss of data.
 
-- **If Ollama is on your computer**, use this command:
+1. **If Ollama is on your computer**, use this command:
 
   ```bash
   docker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:main
   ```
 
-- **If Ollama is on a Different Server**, use this command:
+2. **If Ollama is on a Different Server**, use this command:
 
-- To connect to Ollama on another server, change the `OLLAMA_BASE_URL` to the server's URL:
+  To connect to Ollama on another server, change the `OLLAMA_BASE_URL` to the server's URL:
 
   ```bash
   docker run -d -p 3000:8080 -e OLLAMA_BASE_URL=https://example.com -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:main
   ```
 
-- After installation, you can access Open WebUI at [http://localhost:3000](http://localhost:3000). Enjoy! 😄
+  After installation, you can access Open WebUI at [http://localhost:3000](http://localhost:3000). Enjoy! 😄
 
-- **If you want to customize your build with additional args**, use this commands:
+3. **If you want to customize your build with additional ARGS**, use this commands:
 
-  > [!NOTE]  
-  > If you only want to use Open WebUI with Ollama included or CUDA acelleration it's recomented to use our official images with the tags :cuda or :with-ollama
-  > If you want a combination of both or more customisation options like a different embedding model and/or CUDA version you need to build the image yourself following the instructions below.
+> [!NOTE]  
+> If you only want to use Open WebUI with Ollama included or CUDA acelleration it's recomented to use our official images with the tags :cuda or :ollama
+> If you want a combination of both or more customisation options like a different embedding model and/or CUDA version you need to build the image yourself following the instructions below.
 
-  **For the build:**
+  - **For the build:**
 
   ```bash
   docker build -t open-webui
   ```
 
-  Optional build ARGS (use them in the docker build command below if needed):
+  - **Optional build ARGS (use them in the docker build command below if needed):**
 
-      e.g.
+  e.g.
 
   ```bash
   --build-arg="USE_EMBEDDING_MODEL=intfloat/multilingual-e5-large"
   ```
-
   For "intfloat/multilingual-e5-large" custom embedding model (default is all-MiniLM-L6-v2), only works with [sentence transforer models](https://huggingface.co/models?library=sentence-transformers). Current [Leaderbord](https://huggingface.co/spaces/mteb/leaderboard) of embedding models.
 
   ```bash
   --build-arg="USE_OLLAMA=true"
   ```
-
   For including ollama in the image.
 
   ```bash
   --build-arg="USE_CUDA=true"
   ```
-
   To use CUDA exeleration for the embedding and whisper models.
 
-  > [!NOTE]
-  > You need to install the [Nvidia CUDA container toolkit](https://docs.nvidia.com/dgx/nvidia-container-runtime-upgrade/) on your machine to be able to set CUDA as the Docker engine. Only works with Linux - use WSL for Windows!
+> [!NOTE]
+> You need to install the [Nvidia CUDA container toolkit](https://docs.nvidia.com/dgx/nvidia-container-runtime-upgrade/) on your machine to be able to set CUDA as the Docker engine. Only works with Linux - use WSL for Windows!
 
   ```bash
   --build-arg="USE_CUDA_VER=cu117"
   ```
-
   For CUDA 11 (default is CUDA 12)
 
   **To run the image:**