Update app.py

app.py

@@ -1,15 +1,22 @@
+from transformers import AutoModelForCTC, Wav2Vec2Tokenizer
+import torch
 import gradio as gr
 
-title = "wolof_ASR"
-description = "Wolof ASR"
+model = Wav2Vec2ForCTC.from_pretrained("BenDaouda/wav2vec2-large-xls-r-300m-wolof-test-coloab")
+processor = Wav2Vec2Processor.from_pretrained("BenDaouda/wav2vec2-large-xls-r-300m-wolof-test-coloab")
 
-iface = gr.Interface.load(
-    "BenDaouda/wav2vec2-large-xls-r-300m-wolof-test-coloab",
-    inputs=gr.Audio(source="microphone", type="filepath"),
-    outputs="text",
-    title=title,
-    description=description,
-    enable_queue=True
+def transcribe(audio):
+    input_values = tokenizer(audio, return_tensors="pt").input_values
+    with torch.no_grad():
+        logits = model(input_values).logits
+    predicted_ids = torch.argmax(logits, dim=-1)
+    transcription = tokenizer.batch_decode(predicted_ids)[0]
+    return transcription
+
+iface = gr.Interface(
+    fn=transcribe,
+    inputs=gr.inputs.Audio(source="microphone", type="file", resample_to=16000),
+    outputs="text"
 )
 
 iface.launch()