change default params

Signed-off-by: AnyISalIn <anyisalin@gmail.com>

app.py

@@ -16,6 +16,7 @@ suggestion_checkpoints = [
     "dreamshaper_8_93211.safetensors",
     "epicrealism_pureEvolutionV5_97793.safetensors",
 ]
+base_checkpoints = ["epicrealism_naturalSin_121250", "v1-5-pruned-emaonly"]
 
 
 get_local_storage = """
@@ -53,15 +54,15 @@ def create_ui():
         with gr.Tab(label="Training"):
             with gr.Row():
                 with gr.Column(scale=1):
-                    base_model = gr.Dropdown(choices=["v1-5-pruned-emaonly", "epicrealism_naturalSin_121250"], label="Base Model", value="v1-5-pruned-emaonly")
+                    base_model = gr.Dropdown(choices=base_checkpoints, label="Base Model", value=base_checkpoints[0])
                     geneder = gr.Radio(choices=["man", "woman"], value="man", label="Geneder")
                     training_name = gr.Text(label="Training Name", placeholder="training name", elem_id="training_name", value="my-face-001")
                     max_train_steps = gr.Slider(minimum=200, maximum=4000, step=1, label="Max Train Steps", value=2000)
-                    training_images = gr.File(file_types=["image"], file_count="multiple")
+                    training_images = gr.File(file_types=["image"], file_count="multiple", label="6-10 face images.")
                     training_button = gr.Button(value="Train")
                     training_payload = gr.JSON(label="Training Payload, POST /v3/training/subject")
                 with gr.Column(scale=1):
-                    training_refresh_button = gr.Button(value="Refresh training Status")
+                    training_refresh_button = gr.Button(value="Refresh Training Status")
                     training_refresh_json = gr.JSON()
 
                 def train(novita_key, gender, base_model, training_name, max_train_steps, training_images):
@@ -70,30 +71,39 @@ def create_ui():
                         get_noviata_client(novita_key).create_training_subject(
                             base_model=base_model,
                             name=training_name,
-                            instance_prompt=f"a closeup photo of ohwx {gender}",
+                            instance_prompt=f"a closeup photo of ohwx person",
                             class_prompt="person",
                             max_train_steps=max_train_steps,
                             images=training_images,
+                            components=FACE_TRAINING_DEFAULT_COMPONENTS,
+                            learning_rate=3e-4,
+                            seed=None,
+                            lr_scheduler='cosine_with_restarts',
                             with_prior_preservation=True,
-                            components=FACE_TRAINING_DEFAULT_COMPONENTS
+                            prior_loss_weight=1.0,
+                            lora_r=32,
+                            lora_alpha=32,
+                            lora_text_encoder_r=32,
+                            lora_text_encoder_alpha=32,
                         )
+
                         payload = dict(
                             name=training_name,
                             base_model=base_model,
                             image_dataset_items=["....assets_ids, please manually upload to novita.ai"],
                             expert_setting=TrainingExpertSetting(
-                                instance_prompt=f"a closeup photo of ohwx {gender}",
+                                instance_prompt=f"a closeup photo of ohwx person",
                                 class_prompt="person",
                                 max_train_steps=max_train_steps,
-                                learning_rate=None,
+                                learning_rate="8e-5",
                                 seed=None,
-                                lr_scheduler=None,
+                                lr_scheduler='cosine_with_restarts',
                                 with_prior_preservation=True,
-                                prior_loss_weight=None,
-                                lora_r=None,
-                                lora_alpha=None,
-                                lora_text_encoder_r=None,
-                                lora_text_encoder_alpha=None,
+                                prior_loss_weight=1.0,
+                                lora_r=32,
+                                lora_alpha=32,
+                                lora_text_encoder_r=32,
+                                lora_text_encoder_alpha=32,
                             ),
                             components=[_.to_dict() for _ in FACE_TRAINING_DEFAULT_COMPONENTS],
                         )
@@ -140,7 +150,7 @@ def create_ui():
                         # trained_loras_models = [_.name for _ in get_noviata_client(novita_key).models_v3(refresh=True).filter_by_type("lora").filter_by_visibility("private")]
                         serving_models = [_.models[0].model_name for _ in get_noviata_client(novita_key).list_training().filter_by_model_status("SERVING")]
                         serving_models_labels = [_.task_name for _ in get_noviata_client(novita_key).list_training().filter_by_model_status("SERVING")]
-                        return gr.update(choices=serving_models_labels, value=serving_models_labels[0] if len(serving_models_labels) > 0 else None), gr.update(value=serving_models)
+                        return gr.update(choices=serving_models_labels), gr.update(value=serving_models)
 
                     inference_refresh_button.click(
                         inputs=[novita_key],
@@ -346,7 +356,7 @@ def create_ui():
             except Exception as e:
                 logging.error(e)
                 return novita_key, gr.update(choices=[], value=None), gr.update(value=None), f"$ UNKNOWN"
-            return novita_key, gr.update(choices=serving_models_labels, value=serving_models_labels[0] if len(serving_models_labels) > 0 else None), gr.update(value=serving_models), f"$ {user_info_json.credit_balance / 100 / 100:.2f}"
+            return novita_key, gr.update(choices=serving_models_labels), gr.update(value=serving_models), f"$ {user_info_json.credit_balance / 100 / 100:.2f}"
 
         novita_key.change(onload, inputs=novita_key, outputs=[novita_key, style_lora, _hide_lora_training_response, user_balance], _js="(v)=>{ setStorage('novita_key',v); return [v]; }")