Instructions to use hf-internal-testing/tiny-random-VitsModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-VitsModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="hf-internal-testing/tiny-random-VitsModel")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-VitsModel") model = AutoModelForTextToWaveform.from_pretrained("hf-internal-testing/tiny-random-VitsModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1c562057ea7184505cedc2badb152bf11a02cfe97ea9365a541fda33dea38c75
- Size of remote file:
- 380 kB
- SHA256:
- 888939f46b3a4f46d30ec8cd7f837b2bb7209c165c2c3bf70cf3a6f39e2cfc60
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