Super-squash branch 'main' using huggingface_hub

.gitattributes

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README.md

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+---
+title: Moonshine ASR
+emoji: 🌒
+colorFrom: gray
+colorTo: yellow
+sdk: gradio
+sdk_version: 5.1.0
+app_file: app.py
+pinned: true
+short_description: Fast & efficient ASR outperforming Whisper!
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+ABOUT = """
+# Moonshine ASR
+
+Unofficial demo for [Moonshine ASR](https://github.com/usefulsensors/moonshine) by Useful Sensors, a fast & efficient ASR model outperforming Whisper
+"""
+
+import os
+os.environ["KERAS_BACKEND"] = "torch"
+
+import gradio as gr
+
+import spaces
+
+import moonshine
+
+from pydub import AudioSegment
+
+@spaces.GPU
+def transcribe(audio, chosen_model):
+    audio_file = AudioSegment.from_file(audio)
+    if len(audio_file) / 1000 >= 64:
+        raise gr.Error("Moonshine only supports audio segments up to 64s long. Please pre-segment your audio and try again.")
+    try:
+        transcription = moonshine.transcribe(audio, chosen_model)
+    except Exception as e:
+        raise gr.Error("Moonshine backend error: " + str(e))
+    return ' '.join(transcription).strip()
+
+with gr.Blocks() as demo:
+    gr.Markdown(ABOUT)
+    aud = gr.Audio(label="Audio", type="filepath", interactive=True)
+    modelname = gr.Radio(label="Model", choices=['moonshine/tiny', 'moonshine/base'], value="moonshine/tiny", interactive=True)
+    btn = gr.Button("Transcribe", variant="primary")
+    out = gr.Textbox(label="Transcription", interactive=False)
+    btn.click(transcribe, inputs=[aud, modelname], outputs=out)
+    gr.Markdown("Unofficial demo by [mrfakename](https://x.com/realmrfakename)")
+
+demo.queue().launch()

requirements.txt

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+torch
+torchaudio
+useful-moonshine@git+https://github.com/usefulsensors/moonshine.git
+pydub