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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c6eb7c1d1ff782472580a292b0ad4ae6302536ba6ca9a590538b36b0bd0c155b
- Size of remote file:
- 270 kB
- SHA256:
- 0d65a18798941425afcd636e16226816b4b247d3e3207879b67f080f71ed893c
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