Instructions to use adamchant/dummy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adamchant/dummy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="adamchant/dummy")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("adamchant/dummy") model = AutoModelForTextToSpectrogram.from_pretrained("adamchant/dummy") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 59539064a3a539300b0d396ea72bb97ead837d95e2064c7b0788fe941713692b
- Size of remote file:
- 578 MB
- SHA256:
- d9f04c0ae600b6d25d9ee33b341a92863aff3a72a0a4a767fe00dbcc62785581
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