Instructions to use averrous/subworkout_model_vit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use averrous/subworkout_model_vit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="averrous/subworkout_model_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("averrous/subworkout_model_vit") model = AutoModelForImageClassification.from_pretrained("averrous/subworkout_model_vit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7499e210a2cf961b4fceca5d2f6ad5389391d9eaee47f2430d2433747cb4d639
- Size of remote file:
- 5.11 kB
- SHA256:
- 70e4b031c6f54972de3d1ca44bd443b5850f6ade2465858bb7668dffdc270c55
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