Update app.py

app.py

@@ -457,42 +457,7 @@ with gr.Blocks(theme=theme, css=css) as demo:
             start = gr.Button("Start training", visible=False)
         progress_area = gr.Markdown("")
 
-    with gr.Tab("Train on your device" if is_spaces else "Instructions"):
-        gr.Markdown(f"""To use FLUX LoRA Ease locally with this UI, you can clone this repository (yes, HF Spaces are git repos!). You'll need ~23GB of VRAM
-        ```bash
-        git clone https://huggingface.co/spaces/autotrain-projects/flux-lora-ease
-        cd flux-lora-ease
-        ## Optional, start a venv environment (install torch first) ## 
-        python3 -m venv venv
-        source venv/bin/activate
-        # .\venv\Scripts\activate on windows
-        ## End of optional ##
-        pip install -r requirements_local.txt
-        ```
-        
-        Then you can install ai-toolkit
-        ```bash
-        git clone https://github.com/ostris/ai-toolkit.git
-        cd ai-toolkit
-        git submodule update --init --recursive
-        pip3 install torch
-        pip3 install -r requirements.txt
-        cd ..
-        ```
-
-        Login with Hugging Face to access FLUX.1 [dev], choose a token with `write` permissions to push your LoRAs to the HF Hub
-        ```bash
-        huggingface-cli login
-        ```
-        
-        Finally, you can run FLUX LoRA Ease locally with a UI by doing a simple 
-        ```py
-        python app.py
-        ```
-        
-        If you prefer command line, you can run Ostris' [AI Toolkit](https://github.com/ostris/ai-toolkit) yourself directly.
-        """
-        )
+
 
     dataset_folder = gr.State()