Instructions to use hf-internal-testing/tiny-random-vit-for-testing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-vit-for-testing with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-internal-testing/tiny-random-vit-for-testing") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-vit-for-testing") model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-vit-for-testing") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a63cf64d4d1a24afac3f8f03ed551c6743a1b039ee384b15b8ff90d4155c3dc9
- Size of remote file:
- 276 kB
- SHA256:
- 666092e17d3dbf962457b8e1e0f02d9b15fcf5ab0a0dd8c7256ee7b3898f3dc9
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