Instructions to use hf-internal-testing/tiny-random-SpeechT5Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SpeechT5Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-SpeechT5Model")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-SpeechT5Model") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-SpeechT5Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- be66d7d89ac5f1fb30c8460ef95de48fa2f694bde9fd3bd488fb28e335ff31f8
- Size of remote file:
- 196 kB
- SHA256:
- 69fe9829fb26cb05370b0065f7bf7197d0afb4fd0176af996de63b3619e4e63f
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