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:
- 01a9c0aa2c6003871f1c92b021656715ee11179f46af3195f115b8f2b1a90276
- Size of remote file:
- 4.6 kB
- SHA256:
- 793376bd48e93b08899d1f20f6029ab56e4967d20b123ca69633f54bf6a8339c
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