Instructions to use prithivMLmods/Gym-Workout-Classifier-SigLIP2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Gym-Workout-Classifier-SigLIP2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Gym-Workout-Classifier-SigLIP2") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("prithivMLmods/Gym-Workout-Classifier-SigLIP2") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Gym-Workout-Classifier-SigLIP2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-303/optimizer.pt from prithivMLmods/Gym-Workout-Classifier-SigLIP2: direct link, hf CLI and curl.
- Browser
- Download file 687 MB
-
https://huggingface.co/prithivMLmods/Gym-Workout-Classifier-SigLIP2/resolve/main/checkpoint-303/optimizer.pt
- Command line
-
hf download hf://prithivMLmods/Gym-Workout-Classifier-SigLIP2/checkpoint-303/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/prithivMLmods/Gym-Workout-Classifier-SigLIP2/resolve/main/checkpoint-303/optimizer.pt
687 MB
- Xet hash:
- 951ff45509beb82d6a4368dd83041c62d9002afdf62b98a35e39727e1cad0e89
- Size of remote file:
- 687 MB
- SHA256:
- 9fa5464056762485b7c9b5a43b300c7a2139e71bebf389c30b775ef466fe28d3
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