Instructions to use hf-tiny-model-private/tiny-random-MobileViTForImageClassification 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-MobileViTForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-tiny-model-private/tiny-random-MobileViTForImageClassification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-MobileViTForImageClassification") model = AutoModelForImageClassification.from_pretrained("hf-tiny-model-private/tiny-random-MobileViTForImageClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from hf-tiny-model-private/tiny-random-MobileViTForImageClassification: direct link, hf CLI and curl.
- Browser
- Download file 20.2 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-MobileViTForImageClassification/resolve/main/tf_model.h5
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-MobileViTForImageClassification/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/hf-tiny-model-private/tiny-random-MobileViTForImageClassification/resolve/main/tf_model.h5
20.2 MB
- Xet hash:
- 8a0accba94885d6d09a782995893002720e753bccd6a0bf9b5ca6b099e5e9160
- Size of remote file:
- 20.2 MB
- SHA256:
- e23220721c60b41688e24de5205ec928d5aa6b89c11803735f6af60c15b5ca3a
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