Delete app.py

app.py

@@ -1,24 +0,0 @@
-from datasets import load_dataset, DatasetDict, Audio
-from transformers import WhisperFeatureExtractor, WhisperTokenizer, WhisperProcessor, pipeline
-from transformers import WhisperForConditionalGeneration, Seq2SeqTrainingArguments, Seq2SeqTrainer, WhisperForConditionalGeneration, WhisperProcessor
-from dataclasses import dataclass
-from typing import Any, Dict, List, Union
-import gradio as gr
-import torch
-
-model = WhisperForConditionalGeneration.from_pretrained("hannatoenbreker/whisper-dutch")
-processor = WhisperProcessor.from_pretrained("openai/whisper-small", language="Dutch", task="transcribe")
-pipe = pipeline(model="openai/whisper-small")
-def transcribe(audio):
-    text = pipe(audio)["text"]
-    return text
-
-iface = gr.Interface(
-    fn=transcribe,
-    inputs=gr.Audio(source="microphone", type="filepath"),
-    outputs="text",
-    title="Whisper Small Dutch",
-    description="Realtime demo for Dutch speech recognition using a fine-tuned Whisper small model.",
-)
-
-iface.launch()