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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 298f8fc8f8c332d0c5e0a63696a18a1ab613374c28fee612f7b44ddba8e9f7cb
- Size of remote file:
- 809 kB
- SHA256:
- f0b918426cae8bde3ede71814405c3379e8f4b0b7cbad048a75d9d16a9b6c945
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