Update app.py

app.py

@@ -4,8 +4,9 @@ from typing import Union
 is_spaces = True if os.environ.get("SPACE_ID") else False
 
 if is_spaces:
-    import spaces
     subprocess.run('pip install flash-attn --no-build-isolation', env={'FLASH_ATTENTION_SKIP_CUDA_BUILD': "TRUE"}, shell=True)
+    import spaces
+    
     
 os.environ["HF_HUB_ENABLE_HF_TRANSFER"] = "1"
 import sys
@@ -67,7 +68,7 @@ def load_captioning(uploaded_images, concept_sentence):
 
     # Update for the sample caption area
     updates.append(gr.update(visible=True))
-    updates.append(gr.update(placeholder=f'A photo of {concept_sentence} holding a sign that reads "Hello friend"'))
+    updates.append(gr.update(placeholder=f'A portrait of person in a bustling cafe {concept_sentence}', value=f'A person in a bustling cafe {concept_sentence}'))
     updates.append(gr.update(placeholder=f"A mountainous landscape in the style of {concept_sentence}"))
     updates.append(gr.update(placeholder=f"A {concept_sentence} in a mall"))
     return updates
@@ -221,6 +222,8 @@ theme = gr.themes.Monochrome(
     font=[gr.themes.GoogleFont("Source Sans Pro"), "ui-sans-serif", "system-ui", "sans-serif"],
 )
 css = """
+h1{font-size: 2em}
+h3{margin-top: 0}
 #component-1{text-align:center}
 .main_ui_logged_out{opacity: 0.3; pointer-events: none}
 .tabitem{border: 0px}
@@ -308,7 +311,7 @@ with gr.Blocks(theme=theme, css=css) as demo:
                 lr = gr.Number(label="Learning Rate", value=4e-4, minimum=1e-6, maximum=1e-3, step=1e-6)
                 rank = gr.Number(label="LoRA Rank", value=16, minimum=4, maximum=128, step=4)
 
-            with gr.Accordion("Sample prompts", visible=False) as sample:
+            with gr.Accordion("Sample prompts (optional)", visible=False) as sample:
                 gr.Markdown(
                     "Include sample prompts to test out your trained model. Don't forget to include your trigger word/sentence (optional)"
                 )
@@ -323,12 +326,18 @@ with gr.Blocks(theme=theme, css=css) as demo:
             start = gr.Button("Start training")
         progress_area = gr.Markdown("")
 
-    with gr.Tab("Train locally" if is_spaces else "Instructions"):
+    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!)
+            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/flux-train/flux-lora-trainer
         cd flux-lora-trainer
+        ## Optional, start a venv environment ## 
+        python3 -m venv venv
+        source venv/bin/activate
+        # .\venv\Scripts\activate on windows
+        # install torch first
+        ## End of optional ##
         pip install requirements_local.txt
         ```
         
@@ -337,10 +346,6 @@ with gr.Blocks(theme=theme, css=css) as demo:
         git clone https://github.com/ostris/ai-toolkit.git
         cd ai-toolkit
         git submodule update --init --recursive
-        python3 -m venv venv
-        source venv/bin/activate
-        # .\venv\Scripts\activate on windows
-        # install torch first
         pip3 install torch
         pip3 install -r requirements.txt
         cd ..
@@ -351,10 +356,11 @@ with gr.Blocks(theme=theme, css=css) as demo:
         huggingface-cli login
         ```
         
-        Now you can run FLUX LoRA Ease locally by doing a simple 
+        Now 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.
         """
         )