Creating all the files for a distil-whisper-demo.

README.md

@@ -1,6 +1,6 @@
 ---
 title: Distil Whisper English Transcription
-emoji: 👀
+emoji: ⚡⚡⚡
 colorFrom: green
 colorTo: red
 sdk: gradio

app.py

@@ -0,0 +1,38 @@
+import torch
+from transformers import pipeline
+import gradio as gr
+
+MODEL_NAME = "Shamik/distil-whisper-small-polyAI-minds14"
+
+pipe = pipeline(
+    task="automatic-speech-recognition",
+    model=MODEL_NAME,
+    chunk_length_s=30,
+)
+
+def transcribe(file):
+    outputs = pipe(file) 
+    text = outputs["text"]
+    return text
+
+demo = gr.Interface(
+    fn=transcribe,
+    inputs=[
+        gr.Audio(sources="upload", label="Audio file", type="filepath"),
+    ],
+    outputs="text",
+    title="Distil Whisper English Speech Transcription",
+    description=(
+        "Transcribe long-form audio inputs with the click of a button! Demo uses the"
+        f" checkpoint [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe audio files"
+        " of arbitrary length."
+    ),
+    examples=[
+        ["./example2.flac"],
+        ["./example0.flac"],
+    ],
+    cache_examples=True,
+    allow_flagging="never",
+)
+
+demo.launch()

requirements.txt

@@ -0,0 +1,2 @@
+transformers
+torch