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:
- 25db088e18ce33578216eeaf5fb34ba2ae617b82bcd730b94548c834a142df66
- Size of remote file:
- 436 kB
- SHA256:
- ae1b6e94dada0b6c65ad4339403df0f278bccbb554d6dc3d8922b886a8b52006
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