Update app.py

app.py

@@ -1,62 +1,7 @@
-import torch
-from transformers import pipeline
-from transformers.pipelines.audio_utils import ffmpeg_read
 import gradio as gr
 import os
 
-# Accessing HF_TOKEN key from environment variable
 hf_token = os.environ.get('HF_TOKEN')
 
-device = 0 if torch.cuda.is_available() else "cpu"
-pipe = pipeline("automatic-speech-recognition", model="aslanovaf/wav2vec2-azekb-latest", token=hf_token)
-
-
-def transcribe(file):
-    outputs = pipe(file)
-    text = outputs["text"]
-    return text
-
-demo = gr.Blocks()
-
-mic_transcribe = gr.Interface(
-    fn=transcribe,
-    inputs=[
-        gr.inputs.Audio(source="microphone", type="filepath", optional=True),
-    ],
-    outputs="text",
-    layout="horizontal",
-    theme="huggingface",
-    title="Azerbaijani Fine-Tuned Business Demo: Transcribe Audio",
-    description=(
-        "Transcribe long-form microphone or audio inputs with the click of a button! Demo uses the fine-tuned checkpoint of \
-        [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) and 🤗 Transformers to transcribe audio files."
-    ),
-    allow_flagging="never",
-)
-
-file_transcribe = gr.Interface(
-    fn=transcribe,
-    inputs=[
-        gr.inputs.Audio(source="upload", optional=True, label="Audio file", type="filepath"),
-    ],
-    outputs="text",
-    layout="horizontal",
-    theme="huggingface",
-    title="Azerbaijani Fine-Tuned Business STT Demo: Transcribe Audio",
-    description=(
-        "Transcribe long-form microphone or audio inputs with the click of a button! Demo uses the fine-tuned checkpoint of \
-        [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) and 🤗 Transformers to transcribe audio files."
-    ),
-    examples=[
-        ["./Recording_1.wav", "transcribe"],
-        ["./Recording_2.wav", "transcribe"],
-        ["./Recording_3.wav", "transcribe"]
-    ],
-    cache_examples=True,
-    allow_flagging="never",
-)
-
-with demo:
-    gr.TabbedInterface([mic_transcribe, file_transcribe], ["Transcribe Microphone", "Transcribe Audio File"])
-
-demo.launch(enable_queue=True)
+iface = gr.load(name="aslanovaf/STT_Azerbaijani", hf_token=hf_token, src="spaces")
+iface.queue(api_open=False).launch(show_api=False)