Instructions to use hf-tiny-model-private/tiny-random-ViTHybridForImageClassification 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-ViTHybridForImageClassification 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-ViTHybridForImageClassification") 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-ViTHybridForImageClassification", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1f678f5a6be34af46ffe84dfa8f174963a7880ecbec1519d08547acf113b403b
- Size of remote file:
- 324 kB
- SHA256:
- 40792f773ceac0c697cf1fae7a28be6d220cd22de8f4d8139ae83ef7de3d2c5b
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