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:
- a2ecb97549ca33f77589263a4a52e13c0b08e0f1ee4f9b213a74e0c9b4f1f3de
- Size of remote file:
- 94.6 kB
- SHA256:
- 292801908ffdbef31d4687124ec265cc03313bd0823fccb7bd01a709d996a8f7
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