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.1712414335.a39577a7e444.25850.3
- Xet hash:
- 7a02b42b30a0cb0c0b4bd3c6a43995ba9322d0ee120a8f23daf53eb61fb81332
- Size of remote file:
- 11.5 kB
- SHA256:
- 489c339cf929d2ea2b23dd3cc3185b0b8f5b070e7a22d63e04ab5714d2d4a96d
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