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 pytorch_model.bin from ydshieh/tiny-random-ViTModel: direct link, hf CLI and curl.
- Browser
- Download file 198 kB
-
https://huggingface.co/ydshieh/tiny-random-ViTModel/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ydshieh/tiny-random-ViTModel/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ydshieh/tiny-random-ViTModel/resolve/main/pytorch_model.bin
198 kB
- Xet hash:
- e89cb96df4e03594bcb65cd5253469ca45f75f4719bbbdf1b88f5da06da2ae4c
- Size of remote file:
- 198 kB
- SHA256:
- 953bd47762ae481ab52e0af29c4b529eb2ae46261ba2cd2eb01b458412d11d19
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