update gradio more easy 4

finetune-cli.py

@@ -68,7 +68,7 @@ def main():
         model_cls = DiT
         model_cfg = dict(dim=1024, depth=22, heads=16, ff_mult=2, text_dim=512, conv_layers=4)
         if args.finetune:
-            if args.pretrain == "":
+            if args.pretrain is None:
                 ckpt_path = str(cached_path("hf://SWivid/F5-TTS/F5TTS_Base/model_1200000.pt"))
             else:
                 ckpt_path = args.pretrain
@@ -77,7 +77,7 @@ def main():
         model_cls = UNetT
         model_cfg = dict(dim=1024, depth=24, heads=16, ff_mult=4)
         if args.finetune:
-            if args.pretrain == "":
+            if args.pretrain is None:
                 ckpt_path = str(cached_path("hf://SWivid/E2-TTS/E2TTS_Base/model_1200000.pt"))
             else:
                 ckpt_path = args.pretrain

finetune_gradio.py

@@ -281,6 +281,7 @@ def start_training(
     yield "start train", gr.update(interactive=False), gr.update(interactive=False)
 
     # Command to run the training script with the specified arguments
+    dataset_name = dataset_name.replace("_pinyin", "").replace("_char", "")
     cmd = (
         f"accelerate launch finetune-cli.py --exp_name {exp_name} "
         f"--learning_rate {learning_rate} "
@@ -792,6 +793,7 @@ def check_finetune(finetune):
 def get_checkpoints_project(project_name, is_gradio=True):
     if project_name is None:
         return [], ""
+    project_name = project_name.replace("_pinyin", "").replace("_char", "")
     path_project_ckpts = os.path.join("ckpts", project_name)
 
     if os.path.isdir(path_project_ckpts):