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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8f829106744d1ab470ae3d11751c4c3e8ee4b95289a37f0fb31fcbb8dc864e09
- Size of remote file:
- 436 kB
- SHA256:
- 291de2752588279955edf4b25cacbf2c307c51ae4aab22154714b29281ee4682
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