Instructions to use Splintir/mms-tts-ceb-pld-e30 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Splintir/mms-tts-ceb-pld-e30 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="Splintir/mms-tts-ceb-pld-e30")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("Splintir/mms-tts-ceb-pld-e30") model = AutoModelForTextToWaveform.from_pretrained("Splintir/mms-tts-ceb-pld-e30", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Upload tokenizer
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Upload model
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Ship the data scripts with the checkpoint
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Ship the data scripts with the checkpoint
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initial commit
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