Instructions to use hf-tiny-model-private/tiny-random-VanForImageClassification 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-VanForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-tiny-model-private/tiny-random-VanForImageClassification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModelForImageClassification model = AutoModelForImageClassification.from_pretrained("hf-tiny-model-private/tiny-random-VanForImageClassification", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 364273b698c465a6275afd67a9fd17ddb949c51c33f4c01dab7eb039648610f9
- Size of remote file:
- 1.59 MB
- SHA256:
- e0168a91a28b82877c934bf1f669baa36309e58d1f5063b816b968874b655771
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