Update app.py

app.py

@@ -10,7 +10,8 @@ import torch.nn.functional as F
 from whisperspeech.languages import LANGUAGES
 from whisperspeech.pipeline import Pipeline
 
-title = """#🙋🏻‍♂️ Welcome to🌟Tonic's🌬️💬📝WhisperSpeech
+title = """# 🙋🏻‍♂️ Welcome to🌟Tonic's🌬️💬📝WhisperSpeech
+
 You can use this ZeroGPU Space to test out the current model [🌬️💬📝collabora/whisperspeech](https://huggingface.co/collabora/whisperspeech). 🌬️💬📝collabora/whisperspeech is An Open Source text-to-speech system built by inverting Whisper. Previously known as spear-tts-pytorch. It's like Stable Diffusion but for speech – both powerful and easily customizable.
 You can also use 🌬️💬📝WhisperSpeech by cloning this space. 🧬🔬🔍 Simply click here: <a style="display:inline-block" href="https://huggingface.co/spaces/Tonic/laion-whisper?duplicate=true"><img src="https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14" alt="Duplicate Space"></a></h3> 
 Join us : 🌟TeamTonic🌟 is always making cool demos! Join our active builder's🛠️community 👻  [![Join us on Discord](https://img.shields.io/discord/1109943800132010065?label=Discord&logo=discord&style=flat-square)](https://discord.gg/GWpVpekp) On 🤗Huggingface: [TeamTonic](https://huggingface.co/TeamTonic) & [MultiTransformer](https://huggingface.co/MultiTransformer) On 🌐Github: [Polytonic](https://github.com/tonic-ai) & contribute to 🌟 [Poly](https://github.com/tonic-ai/poly) 🤗Big thanks to Yuvi Sharma and all the folks at huggingface for the community grant 🤗
@@ -34,8 +35,8 @@ def whisper_speech_demo(text, lang, speaker_audio=None, mix_lang=None, mix_text=
 
     with tempfile.NamedTemporaryFile(delete=False, suffix='.wav') as tmp_file:
         tmp_file_name = tmp_file.name
-        audio_np = audio_data.numpy()  # Convert tensor to numpy array
-        sf.write(tmp_file_name, audio_np, 22050)  # Assuming a sample rate of 22050 Hz
+        audio_np = audio_data.numpy()cpu().numpy()
+        sf.write(tmp_file_name, audio_np, 22050)
 
     return tmp_file_name