Instructions to use hf-tiny-model-private/tiny-random-SEWDModel 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-SEWDModel 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-SEWDModel")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-SEWDModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-SEWDModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 333ec51abbcd6612a45d1d4b2f6e79159868c9828292be82020eba32db85c895
- Size of remote file:
- 287 kB
- SHA256:
- 55869ddc65ae26a12fa71c8c014706d66ca73ee4aa37d80784c0d4f96045dc03
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