Instructions to use hf-internal-testing/tiny-random-ViTForImageClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ViTForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-internal-testing/tiny-random-ViTForImageClassification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-ViTForImageClassification") model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-ViTForImageClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-ViTForImageClassification: direct link, hf CLI and curl.
- Browser
- Download file 176 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-ViTForImageClassification/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-ViTForImageClassification@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-ViTForImageClassification/resolve/refs%2Fpr%2F1/model.safetensors
176 kB
- Xet hash:
- 25c7257bc52e00e1e714e0b2f1d907500d5e23ab9019e86157daff3432e772f0
- Size of remote file:
- 176 kB
- SHA256:
- 0d1195c81173cc9130c6ba8e33e05b0c8ef23b1b5cbaa2e0e49e5c1be42f0b27
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