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, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-Speech2TextModel") model = AutoModelForMultimodalLM.from_pretrained("hf-internal-testing/tiny-random-Speech2TextModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- acb83270c8138c5138b6cf60fa16999ae3090a5acd0df164ed97c02546f546a4
- Size of remote file:
- 728 kB
- SHA256:
- c61c956a93398c564ba8d0bf20e5b96f9e931674ce69933e5a8cf26fe4fd24d7
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