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+# WebUI quickstart on Windows
+This quickstart tutorial provides a step-by-step guide on how to use Text-Generation-WebUI to run Hugging Face transformers-based applications on BigDL-LLM.
+
+The WebUI is ported from [Text-Generation-WebUI](https://github.com/oobabooga/text-generation-webui).
+
+## 1. Install and set up WebUI
+
+### 1.1 Install GPU driver
+* Download and Install Visual Studio 2022 Community Edition from the [official Microsoft Visual Studio website](https://visualstudio.microsoft.com/downloads/). Ensure you select the **Desktop development with C++ workload** during the installation process.
+   
+    > Note: The installation could take around 15 minutes, and requires at least 7GB of free disk space.  
+    > If you accidentally skip adding the **Desktop development with C++ workload** during the initial setup, you can add it afterward by navigating to **Tools > Get Tools and Features...**. Follow the instructions on [this Microsoft guide](https://learn.microsoft.com/en-us/cpp/build/vscpp-step-0-installation?view=msvc-170#step-4---choose-workloads)  to update your installation.
+    > 
+    > <img src="https://llm-assets.readthedocs.io/en/latest/_images/quickstart_windows_gpu_1.png" alt="image-20240221102252560" width=100%; />
+
+* Download and install the latest GPU driver from the [official Intel download page](https://www.intel.com/content/www/us/en/download/785597/intel-arc-iris-xe-graphics-windows.html). A system reboot is necessary to apply the changes after the installation is complete.
+   
+    > Note: The process could take around 10 minutes. After reboot, check for the **Intel Arc Control** application to verify the driver has been installed correctly. If the installation was successful, you should see the **Arc Control** interface similar to the figure below
+
+    > <img src="https://llm-assets.readthedocs.io/en/latest/_images/quickstart_windows_gpu_3.png" width=80%; />
+
+* To monitor your GPU's performance and status, you can use either the **Windows Task Manager** (see the left side of the figure below) or the **Arc Control** application (see the right side of the figure below) :
+    >  <img src="https://llm-assets.readthedocs.io/en/latest/_images/quickstart_windows_gpu_4.png"  width=70%; />
+
+### 1.2 Set up Python Environment
+
+* Visit [Miniconda installation page](https://docs.anaconda.com/free/miniconda/), download the **Miniconda installer for Windows**, and follow the instructions to complete the installation.
+
+  <!-- > <img src="https://llm-assets.readthedocs.io/en/latest/_images/quickstart_windows_gpu_5.png"  width=50%; /> -->
+
+* After installation, open the **Anaconda Prompt**, create a new python environment `llm`:
+  ```bash
+  conda create -n llm python=3.9 libuv
+  ```
+* Activate the newly created environment `llm`:
+  ```bash
+  conda activate llm
+  ```
+
+### 1.3 Install oneAPI and `bigdl-llm`
+
+* With the `llm` environment active, use `pip` to install the [**Intel oneAPI Base Toolkit**](https://www.intel.com/content/www/us/en/developer/tools/oneapi/overview.html):
+  ```bash
+  pip install dpcpp-cpp-rt==2024.0.2 mkl-dpcpp==2024.0.0 onednn==2024.0.0
+  ```
+
+* Use `pip` to install `bigdl-llm` for GPU:
+  ```bash
+  pip install --pre --upgrade bigdl-llm[xpu] -f https://developer.intel.com/ipex-whl-stable-xpu
+  ```
+
+### 1.4 Download WebUI
+Download text-generation-webui with `BigDL-LLM` optimizations from [here](https://github.com/intel-analytics/text-generation-webui/archive/refs/heads/bigdl-llm.zip) and unzip it to a folder. In this example, the text-generation-webui folder is `C:\text-generation-webui`
+  
+### 1.5 Install other dependencies
+In your **Anaconda Prompt** terminal, navigate to your unzipped text-generation-webui folder. Then use `pip` to install other WebUI dependencies:
+```bash
+pip install -r requirements_cpu_only.txt
+```
+
+## 2. Start the WebUI Server
+
+* Step 1: Open the **Anaconda Prompt** and activate the Python environment `llm` you previously created: 
+   ```bash
+   conda activate llm
+   ```
+
+* Step 2: If you're running on iGPU, set some environment variables by running below commands:
+  > For more details about runtime configurations, refer to [this guide](https://bigdl.readthedocs.io/en/latest/doc/LLM/Overview/install_gpu.html#runtime-configuration): 
+  ```bash
+  set SYCL_CACHE_PERSISTENT=1
+  set BIGDL_LLM_XMX_DISABLED=1
+  ```
+
+* Step 3: Navigate to your unzipped text-generation-webui folder (`C:\text-generation-webui` in this example) and launch webUI. Models will be optimized and run at 4-bit precision.
+   ```bash
+   cd C:\text-generation-webui
+   python server.py --load-in-4bit
+   ```
+
+* Step 4: After the successful startup of the WebUI server, links to access WebUI are displayed in the terminal.
+  <!-- ```bash
+  Running on local URL:  http://127.0.0.1:7860
+  ``` -->
+  <img src="https://llm-assets.readthedocs.io/en/latest/_images/webui_quickstart_launch_server.png" width=80%; />
+
+  Open the local URL (eg., http://127.0.0.1:7864) in your web browser to access the webUI interface.
+
+## 3. Using WebUI
+
+### 3.1 Select the Model
+
+First, you need to place huggingface models in `C:\text-generation-webui\models`.
+You can either copy a local model to that folder, or download a model from Huggingface Hub using webUI (VPN connection might be required).
+To download a model, navigate to `Model` tab, enter the Huggingface model `username/model path` under `Download model or LoRA` (for instance, `Qwen/Qwen-7B-Chat`), and click `Download`.
+
+<img src="https://llm-assets.readthedocs.io/en/latest/_images/webui_quickstart_download_model.png" width=80%; />
+
+After the models have been obtained, click the blue icon to refresh the `Model` drop-down list.
+Then select the model you want from the list.
+
+<img src="https://llm-assets.readthedocs.io/en/latest/_images/webui_quickstart_select_model.png" width=80%; />
+
+
+### 3.2 Load the Model
+Using the default model settings are recommended. 
+Click `Load` to load your model.
+
+* For some modes, you might see an `ImportError: This modeling file requires the following packages that were not found in your environment` error message (scroll down to the end of the error messages) and instructions for installing the packages. This is because the models require additional pip packages.
+Stop the WebUI Server in the **Anaconda Prompt** terminal with `Ctrl+C`, install the pip packages, and then run the WebUI Server again.
+If there are still errors on missing packages, repeat the process of installing missing packages.
+
+* Some models are too old and do not support the installed version of transformers package. 
+In this case, errors like `AttributeError`, would appear. You are should use a more recent model.
+
+<img src="https://llm-assets.readthedocs.io/en/latest/_images/webui_quickstart_load_model_error.png" width=80%; />
+
+When the model is successfully loaded, you will get a message on this.
+
+<img src="https://llm-assets.readthedocs.io/en/latest/_images/webui_quickstart_load_model_success.png" width=80%; />
+
+### 3.3 Run the Model on WebUI
+Select the `Chat` tab. This interface supports having multi-turn conversations with the model. 
+You may simply enter prompts and click the `Generate` button to get responses.
+You can start a new conversation by clicking `New chat`.
+
+<img src="https://llm-assets.readthedocs.io/en/latest/_images/webui_quickstart_chat.png" width=80%; />
+
+<!-- Notes:
+* Multi-turn conversations may consume GPU memory. You may specify the `Truncate the prompt up to this length` value in `Parameters` tab to reduce the GPU memory usage.
+
+* You may switch to a single-turn conversation mode by turning off `Activate text streaming` in the Parameters tab.
+
+* Please see [Chat-Tab Wiki](https://github.com/oobabooga/text-generation-webui/wiki/01-%E2%80%90-Chat-Tab) for more details. -->
+
+### 3.4 Ending the program
+Go to the **Anaconda Prompt** terminal where the WebUI Server was launched, enter `Ctrl+C` to stop the server. 
+Then close the webUI browser tab.
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