Instructions to use hf-tiny-model-private/tiny-random-MobileViTModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-MobileViTModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-tiny-model-private/tiny-random-MobileViTModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-MobileViTModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-MobileViTModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-tiny-model-private/tiny-random-MobileViTModel: direct link, hf CLI and curl.
- Browser
- Download file 19.9 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-MobileViTModel/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-MobileViTModel/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-tiny-model-private/tiny-random-MobileViTModel/resolve/main/pytorch_model.bin
19.9 MB
- Xet hash:
- 222564c84f190f752046015e1b78f0ec7288ab9a078fc822ce1a0cf86547c51a
- Size of remote file:
- 19.9 MB
- SHA256:
- 7b1d1c78553e36680307ed5451c74d4e9596711a26142815ebc71a1f9c1b50e0
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