Instructions to use cortexsgea/sonus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cortexsgea/sonus with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="cortexsgea/sonus")# Load model directly from transformers import OmniVoice model = OmniVoice.from_pretrained("cortexsgea/sonus", dtype="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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from transformers import AutoModel, AutoTokenizer
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import torch
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model = AutoModel.from_pretrained("
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tokenizer = AutoTokenizer.from_pretrained("
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# Load to device
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model = model.to("cuda")
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from transformers import AutoModel, AutoTokenizer
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import torch
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model = AutoModel.from_pretrained("cortexsgea/sonus", trust_remote_code=True)
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tokenizer = AutoTokenizer.from_pretrained("cortexsgea/sonus", trust_remote_code=True)
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# Load to device
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model = model.to("cuda")
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