Instructions to use ydshieh/tiny-random-ViTModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ydshieh/tiny-random-ViTModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="ydshieh/tiny-random-ViTModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("ydshieh/tiny-random-ViTModel") model = AutoModel.from_pretrained("ydshieh/tiny-random-ViTModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from ydshieh/tiny-random-ViTModel: direct link, hf CLI and curl.
- Browser
- Download file 291 kB
-
https://huggingface.co/ydshieh/tiny-random-ViTModel/resolve/main/tf_model.h5
- Command line
-
hf download hf://ydshieh/tiny-random-ViTModel/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/ydshieh/tiny-random-ViTModel/resolve/main/tf_model.h5
291 kB
- Xet hash:
- 81a26811eee1f42c20da483148e0670c753c8e98a974da265adbf4a47cfb5f56
- Size of remote file:
- 291 kB
- SHA256:
- 945b6d03a0bfe41e43cd0f9d5d9c90f48f56210eb8b801008a03f6c9a5a56348
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