Instructions to use hf-internal-testing/tiny-random-Speech2TextModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Speech2TextModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-Speech2TextModel")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-Speech2TextModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-Speech2TextModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7000c079d12ab0b78da14c42caf4e256b05a4f1c95a9949e16123b0d086417dd
- Size of remote file:
- 746 kB
- SHA256:
- 0b042f39bdc8116cee3120e332a5b45d0c103f4e4b41670edd5251f9567e8dff
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