Instructions to use hf-tiny-model-private/tiny-random-VanModel 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-VanModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-tiny-model-private/tiny-random-VanModel")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-VanModel", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6451393ac50fd30cb93618208cdb4094e8d4d08129f9abab68663b8a6cc9a93b
- Size of remote file:
- 1.56 MB
- SHA256:
- 3ed096880f3826e05e6725216fded8de7c81965831c2b92a7b423561026ed994
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