Instructions to use suno/bark-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use suno/bark-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="suno/bark-small")# Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("suno/bark-small") model = AutoModelForTextToWaveform.from_pretrained("suno/bark-small") - Notebooks
- Google Colab
- Kaggle
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README.md
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synthesiser = pipeline("text-to-speech", "suno/bark-small")
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speech =
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scipy.io.wavfile.write("bark_out.wav", rate=speech["sampling_rate"], data=speech["audio"])
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```
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synthesiser = pipeline("text-to-speech", "suno/bark-small")
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speech = synthesiser("Hello, my dog is cooler than you!", forward_params={"do_sample": True})
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scipy.io.wavfile.write("bark_out.wav", rate=speech["sampling_rate"], data=speech["audio"])
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```
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