Updated model list

app.py

@@ -2,57 +2,70 @@ import gradio as gr
 
 from transformers import pipeline
 
-DEFAULT_MODEL = "ginic/data_seed_4_wav2vec2-large-xlsr-buckeye-ipa"
+DEFAULT_MODEL = "ginic/data_seed_bs64_4_wav2vec2-large-xlsr-53-buckeye-ipa"
+
 
 VALID_MODELS = [
     "ctaguchi/wav2vec2-large-xlsr-japlmthufielta-ipa-plus-2000",
-    "ginic/hyperparam_tuning_1_wav2vec2-large-xlsr-buckeye-ipa",
-    "ginic/data_seed_1_wav2vec2-large-xlsr-buckeye-ipa",
-    "ginic/data_seed_2_wav2vec2-large-xlsr-buckeye-ipa",
-    "ginic/data_seed_3_wav2vec2-large-xlsr-buckeye-ipa",
-    "ginic/data_seed_4_wav2vec2-large-xlsr-buckeye-ipa",
-    "ginic/gender_split_30_female_1_wav2vec2-large-xlsr-buckeye-ipa",
-    "ginic/gender_split_30_female_2_wav2vec2-large-xlsr-buckeye-ipa",
-    "ginic/gender_split_30_female_3_wav2vec2-large-xlsr-buckeye-ipa",
-    "ginic/gender_split_30_female_4_wav2vec2-large-xlsr-buckeye-ipa",
-    "ginic/gender_split_30_female_5_wav2vec2-large-xlsr-buckeye-ipa",
-    "ginic/gender_split_70_female_1_wav2vec2-large-xlsr-buckeye-ipa",
-    "ginic/gender_split_70_female_2_wav2vec2-large-xlsr-buckeye-ipa",
-    "ginic/gender_split_70_female_3_wav2vec2-large-xlsr-buckeye-ipa",
-    "ginic/gender_split_70_female_4_wav2vec2-large-xlsr-buckeye-ipa",
-    "ginic/gender_split_70_female_5_wav2vec2-large-xlsr-buckeye-ipa",
-    "ginic/vary_individuals_old_only_1_wav2vec2-large-xlsr-buckeye-ipa",
-    "ginic/vary_individuals_old_only_2_wav2vec2-large-xlsr-buckeye-ipa",
-    "ginic/vary_individuals_old_only_3_wav2vec2-large-xlsr-buckeye-ipa",
-    "ginic/vary_individuals_young_only_1_wav2vec2-large-xlsr-buckeye-ipa",
-    "ginic/vary_individuals_young_only_2_wav2vec2-large-xlsr-buckeye-ipa",
-    "ginic/vary_individuals_young_only_3_wav2vec2-large-xlsr-buckeye-ipa"
+    "ginic/data_seed_bs64_1_wav2vec2-large-xlsr-53-buckeye-ipa",
+    "ginic/data_seed_bs64_2_wav2vec2-large-xlsr-53-buckeye-ipa",
+    "ginic/data_seed_bs64_3_wav2vec2-large-xlsr-53-buckeye-ipa",
+    "ginic/data_seed_bs64_4_wav2vec2-large-xlsr-53-buckeye-ipa",
+    "ginic/gender_split_30_female_1_wav2vec2-large-xlsr-53-buckeye-ipa",
+    "ginic/gender_split_30_female_2_wav2vec2-large-xlsr-53-buckeye-ipa",
+    "ginic/gender_split_30_female_3_wav2vec2-large-xlsr-53-buckeye-ipa",
+    "ginic/gender_split_30_female_4_wav2vec2-large-xlsr-53-buckeye-ipa",
+    "ginic/gender_split_30_female_5_wav2vec2-large-xlsr-53-buckeye-ipa",
+    "ginic/gender_split_70_female_1_wav2vec2-large-xlsr-53-buckeye-ipa",
+    "ginic/gender_split_70_female_2_wav2vec2-large-xlsr-53-buckeye-ipa",
+    "ginic/gender_split_70_female_3_wav2vec2-large-xlsr-53-buckeye-ipa",
+    "ginic/gender_split_70_female_4_wav2vec2-large-xlsr-53-buckeye-ipa",
+    "ginic/gender_split_70_female_5_wav2vec2-large-xlsr-53-buckeye-ipa",
+    
 ]
 
+
 def load_model_and_predict(model_name, audio_in, model_state):
     if model_state["model_name"] != model_name:
-        model_state = {"loaded_model":pipeline(task="automatic-speech-recognition", model=model_name), 
-                       "model_name": model_name}
-    
+        model_state = {
+            "loaded_model": pipeline(
+                task="automatic-speech-recognition", model=model_name
+            ),
+            "model_name": model_name,
+        }
+
     return model_state["loaded_model"](audio_in)["text"], model_state
 
+
 def launch_demo():
-    initial_model = {"loaded_model":pipeline(task="automatic-speech-recognition", model=DEFAULT_MODEL), 
-                    "model_name": DEFAULT_MODEL}
-    demo= gr.Interface(
-        fn=load_model_and_predict, 
-        inputs= [
-            gr.Dropdown(VALID_MODELS, value=DEFAULT_MODEL, label="IPA transcription ASR model", info="Select the model to use for prediction."),
+    initial_model = {
+        "loaded_model": pipeline(
+            task="automatic-speech-recognition", model=DEFAULT_MODEL
+        ),
+        "model_name": DEFAULT_MODEL,
+    }
+    demo = gr.Interface(
+        fn=load_model_and_predict,
+        inputs=[
+            gr.Dropdown(
+                VALID_MODELS,
+                value=DEFAULT_MODEL,
+                label="IPA transcription ASR model",
+                info="Select the model to use for prediction.",
+            ),
             gr.Audio(type="filepath"),
-            gr.State(value=initial_model) #Store the name of the currently loaded model
-        ],  
+            gr.State(
+                value=initial_model
+            ),  # Store the name of the currently loaded model
+        ],
         outputs=[gr.Textbox(label="Predicted IPA transcription"), gr.State()],
         allow_flagging="never",
         title="Automatic International Phonetic Alphabet Transcription",
-        description="This demo allows you to experiment with producing phonetic transcriptions of uploaded or recorded audio using a selected automatic speech recognition (ASR) model."
+        description="This demo allows you to experiment with producing phonetic transcriptions of uploaded or recorded audio using a selected automatic speech recognition (ASR) model.",
     )
 
     demo.launch()
 
+
 if __name__ == "__main__":
-    launch_demo()
+    launch_demo()