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:
- 7160fa7e385123b9ef5d0bb44bce6a9981e9391d58b0e9b32c2e94b6ad5c046c
- Size of remote file:
- 1.56 MB
- SHA256:
- f276f810b2829492946518287558179eb17cbeb7ab43bd1ee70dc78f0ea758ce
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