Instructions to use hf-internal-testing/tiny-random-vit 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 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") 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") model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-vit") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): f7dbfaa
Update config.json
Browse files- config.json +4 -1
config.json
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"num_hidden_layers": 5,
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"patch_size": 2,
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"transformers_version": "4.11.0.dev0",
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"vocab_size": {}
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}
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"num_hidden_layers": 5,
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"patch_size": 2,
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"transformers_version": "4.11.0.dev0",
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"vocab_size": {},
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"architectures": [
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"ViTForImageClassification"
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]
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}
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