Instructions to use Matthijs/mms-tts-abi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Matthijs/mms-tts-abi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="Matthijs/mms-tts-abi")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("Matthijs/mms-tts-abi") model = AutoModelForTextToWaveform.from_pretrained("Matthijs/mms-tts-abi") - Notebooks
- Google Colab
- Kaggle
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README.md
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Audio(output.audio[0], rate=16000)
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[uroman](https://github.com/isi-nlp/uroman) tool.
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## Model credits
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Audio(output.audio[0], rate=16000)
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```
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## Model credits
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