Instructions to use kubicra/checkpoints_and_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kubicra/checkpoints_and_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="kubicra/checkpoints_and_output")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("kubicra/checkpoints_and_output") model = AutoModelForTextToSpectrogram.from_pretrained("kubicra/checkpoints_and_output") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4e9e5ca08e123be48fa478ee0902e32908a7a25989299c27941628c24ff936bc
- Size of remote file:
- 5.5 kB
- SHA256:
- ba0cb1e403d1e6bf0a302bcaf39566685d346cfb3f588a94bd73fcea534e8f89
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