Instructions to use luciagil/Human-action-convnext with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use luciagil/Human-action-convnext with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="luciagil/Human-action-convnext") 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("luciagil/Human-action-convnext") model = AutoModelForImageClassification.from_pretrained("luciagil/Human-action-convnext", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Human-action-convnext / runs /Apr06_14-19-59_a39577a7e444 /events.out.tfevents.1712413382.a39577a7e444.25850.0
- Xet hash:
- 4de1b431007e3e72d0b431bcb080d4be5939f6c507e63b8df976efb9d51cec88
- Size of remote file:
- 15.8 kB
- SHA256:
- 99d1b7d5010dfb01fb40a8251a1c590962cc4032227d8c1c2c890ad085475de2
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