Instructions to use hf-internal-testing/tiny-random-ViTMSNForImageClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ViTMSNForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-internal-testing/tiny-random-ViTMSNForImageClassification") 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-ViTMSNForImageClassification") model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-ViTMSNForImageClassification") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
by SFconvertbot - opened
- model.safetensors +3 -0
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version https://git-lfs.github.com/spec/v1
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oid sha256:f4e771742a006661115a83b0efabc7c47cb1b09cb8b95efe33ed22ea0419abf2
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size 176460
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