Instructions to use hf-internal-testing/tiny-random-VanForImageClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-VanForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-internal-testing/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-internal-testing/tiny-random-VanForImageClassification", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c4457403d0bf4f4f06d36f2f69da659572928e07d17cae7f3892160d0cce96d3
- Size of remote file:
- 1.59 MB
- SHA256:
- 769cf21e6e065dc0e0fe08b24cc3274e51c453b5db827b9dcd9be7f676b6d233
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