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:
- dfaf77fc3841430fbafc0bf341c027e714b118fd4ce977e9aefc063b644315ef
- Size of remote file:
- 321 kB
- SHA256:
- c05c335480e4b0665d915e1d604cea973b10bed5458aee6cd2b0b372595fdeac
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