Instructions to use hf-tiny-model-private/tiny-random-Speech2TextModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-Speech2TextModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-Speech2TextModel")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-Speech2TextModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-Speech2TextModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d7ad3f65c8ce77d89ad89158f6b5dc230a367b4ec7ebd3e4eac86cbf106d8015
- Size of remote file:
- 728 kB
- SHA256:
- 517096920c10767ea44acf566807d59fc9874f2c7f21b617cfbf84d3c0f5e8fb
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