Change from_wav to from_file

app.py

@@ -20,10 +20,11 @@ current_model = "mt3"
 
 def change_model(model):
     global current_model
+    checkpoint_path = f"/content/checkpoints/{model}/"
     if model == current_model:
         return
     global inference_model 
-    inference_model = InferenceModel("/home/user/app/checkpoints/mt3/", model)
+    inference_model = InferenceModel(checkpoint_path, model)
     current_model = model
     print("Inferece model", inference_model)
 
@@ -37,11 +38,12 @@ def get_audio(url):
     os.rename(out_file, new_file)
     a = new_file
     print("file a is:", a)
-    wav_to_cut = AudioSegment.from_wav(a)
+    wav_to_cut = AudioSegment.from_file(a)
     # pydub does things in milliseconds
     ten_seconds = 10 * 1000
     first_10_seconds = wav_to_cut[:ten_seconds]
     os.remove(new_file)
+    os.remove(a)
     return first_10_seconds
 
 # Credits https://huggingface.co/spaces/jeffistyping/Youtube-Whisperer
@@ -66,7 +68,7 @@ title = "Transcribe music from YouTube videos using Transformers."
 description = """
 Gradio demo for Music Transcription with Transformers. Read more in the links below.
 """
-article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2111.03017' target='_blank'>MT3: Multi-Task Multitrack Music Transcription</a> | <a href='https://github.com/magenta/mt3' target='_blank'>Github Repo</a></p>"
+article = "<p style='text-align: center'><a href='https://magenta.tensorflow.org/transcription-with-transformers' target='_blank'>Blog: Music Transcription with Transformers</a> | <a href='https://github.com/magenta/mt3' target='_blank'>Github Repo</a></p>"
 
 # Create a block object
 demo = gr.Blocks()