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:
- 1bc2e8d5b605f6515bd142992a3a4aba6d26022e81906f209bd8ef67848f9da8
- Size of remote file:
- 436 kB
- SHA256:
- 13f7a9d477853d34b94e1c1b00eaca0468396bea97210eb378fb851534465d2c
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