Update app.py

app.py

@@ -3,6 +3,7 @@ import subprocess
 from typing import Union
 from huggingface_hub import whoami
 is_spaces = True if os.environ.get("SPACE_ID") else False
+is_canonical = True if os.environ.get("SPACE_ID") == "autotrain-projects/train-flux-lora-ease" else False
 
 if is_spaces:
     subprocess.run('pip install flash-attn --no-build-isolation', env={'FLASH_ATTENTION_SKIP_CUDA_BUILD': "TRUE"}, shell=True)
@@ -226,7 +227,7 @@ def start_training(
     else:
         config["config"]["process"][0]["train"]["disable_sampling"] = True
         
-    if(which_model == "[schnell] (4 step fast model)"):
+    if(which_model == "[schnell]"):
         config["config"]["process"][0]["model"]["name_or_path"] = "black-forest-labs/FLUX.1-schnell"
         config["config"]["process"][0]["model"]["assistant_lora_path"] = "ostris/FLUX.1-schnell-training-adapter"
         config["config"]["process"][0]["sample"]["sample_steps"] = 4
@@ -374,7 +375,13 @@ with gr.Blocks(theme=theme, css=css) as demo:
                         placeholder="uncommon word like p3rs0n or trtcrd, or sentence like 'in the style of CNSTLL'",
                         interactive=True,
                     )
-                which_model = gr.Radio(["[schnell] (4 step fast model)", "[dev] (high quality model, non-commercial license - available when training locally)"], label="Which base model to train?", elem_id="space_model" if is_spaces else "local_model", value="[schnell] (4 step fast model)",)
+                which_model = gr.Radio(
+                    [("[schnell] (4 step fast model)", "[schnell]"),
+                     ("[dev] (high quality model, non-commercial license - available if you duplicate this space or locally)" if is_canonical else "[dev] (high quality model, non-commercial license)", "[dev]")],
+                    label="Which base model to train?",
+                    elem_id="space_model" if is_canonical else "local_model",
+                    value="[schnell]" if is_canonical else "[dev]"
+                )
                 model_warning = gr.Markdown("""> [dev] model license is non-commercial. By choosing to fine-tune [dev], you must agree with [its license](https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md) and make sure the LoRA you will train and the training process you would start does not violate it.
                 """, visible=False)
             with gr.Group(visible=True) as image_upload: