Subindo arquivos131

app.py

@@ -1,7 +1,7 @@
 import gradio as gr
 import torch
 import numpy as np
-from transformers import Wav2Vec2Processor
+from transformers import Wav2Vec2Processor, Wav2Vec2ForSequenceClassification
 from safetensors.torch import load_file
 
 # Carregar o modelo e o processador salvos
@@ -9,7 +9,8 @@ model_name = "results"
 processor = Wav2Vec2Processor.from_pretrained(model_name)
 
 # Carregar o modelo do arquivo safetensors
-model = load_file("results/model.safetensors")
+state_dict = load_file("results/model.safetensors")
+model = Wav2Vec2ForSequenceClassification.from_pretrained(model_name, state_dict=state_dict)
 
 def classify_accent(audio):
     if audio is None:
@@ -22,8 +23,8 @@ def classify_accent(audio):
     print(f"Entrada de audio recibida: {audio}")
 
     try:
-        audio_array = audio[1]  # O áudio da tupla
-        sample_rate = audio[0]  # A taxa de amostragem da tupla
+        audio_array = audio["array"]  # O áudio da tupla
+        sample_rate = audio["sampling_rate"]  # A taxa de amostragem da tupla
 
         print(f"Forma del audio: {audio_array.shape}, Frecuencia de muestreo: {sample_rate}")
 
@@ -58,7 +59,7 @@ description_html = """
 # Interface do Gradio
 interface = gr.Interface(
     fn=classify_accent,
-    inputs=gr.Audio(type="numpy"),
+    inputs=gr.Audio(type="numpy", source="microphone"),
     outputs="label",
     title="Clasificador de Sotaques (Español vs Otro)",
     description=description_html