test

app.py

@@ -1,16 +1,20 @@
 import gradio as gr
-from transformers import pipeline
+import transformers
 
 pipeline = pipeline("audio-classification", model="DanielDBGC/my_awesome_lang_class_mind_model")
 
 def predict(input_sound):
-    predictions = pipeline(input_sound)
+    dataset = load_dataset("PolyAI/minds14", name="en-US", split="train")
+    dataset = dataset.cast_column("audio", Audio(sampling_rate=16000))
+    sampling_rate = dataset.features["audio"].sampling_rate
+    audio_file = dataset[0]["audio"]["path"]
+    predictions = pipeline(audio_file)
     return {p["label"]: p["score"] for p in predictions} 
 
 gradio_app = gr.Interface(
     predict,
-    inputs=gr.Audio(label="Record or upload someone speaking!", sources=['upload', 'microphone'], type = 'numpy'),
-    outputs=[gr.Label(label="Result", num_top_classes=3)],
+    inputs= 'Test' #gr.Audio(label="Record or upload someone speaking!", sources=['upload', 'microphone'], type = 'numpy'),
+    outputs=#[gr.Label(label="Result", num_top_classes=3)],
     title="Guess the language!",
 )