Instructions to use Indus-Labs/indus-pocket-tts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Pocket-TTS
How to use Indus-Labs/indus-pocket-tts with Pocket-TTS:
from pocket_tts import TTSModel import scipy.io.wavfile tts_model = TTSModel.load_model("Indus-Labs/indus-pocket-tts") voice_state = tts_model.get_state_for_audio_prompt( "hf://kyutai/tts-voices/alba-mackenna/casual.wav" ) audio = tts_model.generate_audio(voice_state, "Hello world, this is a test.") # Audio is a 1D torch tensor containing PCM data. scipy.io.wavfile.write("output.wav", tts_model.sample_rate, audio.numpy()) - Notebooks
- Google Colab
- Kaggle
Download samples/07_long_explanation.mp3 from Indus-Labs/indus-pocket-tts: direct link, hf CLI and curl.
- Browser
- Download file 157 kB
-
https://huggingface.co/Indus-Labs/indus-pocket-tts/resolve/main/samples/07_long_explanation.mp3
- Command line
-
hf download hf://Indus-Labs/indus-pocket-tts/samples/07_long_explanation.mp3
-
curl -L -o 07_long_explanation.mp3 https://huggingface.co/Indus-Labs/indus-pocket-tts/resolve/main/samples/07_long_explanation.mp3
157 kB
- Xet hash:
- 6fe7a3f8853f60bbc5fc922873c544e7147b03bb3cda34856621c18ded282e2c
- Size of remote file:
- 157 kB
- SHA256:
- a69ac8c6494b4151e549f59f097cddeeb1b5d038526441e07c670dcb83360c98
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