Instructions to use hf-tiny-model-private/tiny-random-NatModel 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-NatModel 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-NatModel")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-NatModel", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1a28d2826d2cb44a23b0a1107165866346c69205e6a658e183482ba5bc9d3e2e
- Size of remote file:
- 338 kB
- SHA256:
- 861b11f16b004686e232d0d9628cec15083a8b20b96fcc38296f06bf9963a315
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