Update app.py

app.py

@@ -1,28 +1,28 @@
-import gradio as gr
-from transformers import Speech2TextProcessor, Speech2TextForConditionalGeneration
-import librosa
-import torch
-
-# Cargar el modelo
-repo_name = "HugoZeballos/rapa_nui_asr"  # Ajusta al nombre de tu modelo en Hugging Face
-processor = Speech2TextProcessor.from_pretrained(repo_name)
-model = Speech2TextForConditionalGeneration.from_pretrained(repo_name).to("cuda")
-
-def transcribe(audio_path):
-    audio, sr = librosa.load(audio_path, sr=16000)
-    inputs = processor(audio, sampling_rate=sr, return_tensors="pt", padding="longest").to("cuda")
-
-    with torch.no_grad():
-        predicted_ids = model.generate(inputs["input_features"], attention_mask=inputs["attention_mask"])
-    transcription = processor.batch_decode(predicted_ids, skip_special_tokens=True)[0]
-    return transcription
-
-# Crear interfaz Gradio
-interface = gr.Interface(
-    fn=transcribe,
-    inputs=gr.Audio(source="upload", type="filepath"),
-    outputs="text",
-    title="Transcriptor ASR Rapa Nui"
-)
-
+import gradio as gr
+from transformers import Speech2TextProcessor, Speech2TextForConditionalGeneration
+import librosa
+import torch
+
+# Cargar el modelo
+repo_name = "HugoZeballos/rapa_nui_asr_2"  # Ajusta al nombre de tu modelo en Hugging Face
+processor = Speech2TextProcessor.from_pretrained(repo_name)
+model = Speech2TextForConditionalGeneration.from_pretrained(repo_name).to("cuda")
+
+def transcribe(audio_path):
+    audio, sr = librosa.load(audio_path, sr=16000)
+    inputs = processor(audio, sampling_rate=sr, return_tensors="pt", padding="longest").to("cuda")
+
+    with torch.no_grad():
+        predicted_ids = model.generate(inputs["input_features"], attention_mask=inputs["attention_mask"])
+    transcription = processor.batch_decode(predicted_ids, skip_special_tokens=True)[0]
+    return transcription
+
+# Crear interfaz Gradio
+interface = gr.Interface(
+    fn=transcribe,
+    inputs=gr.Audio(source="upload", type="filepath"),
+    outputs="text",
+    title="Transcriptor ASR Rapa Nui"
+)
+
 interface.launch()