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_14-47-21_a39577a7e444 /events.out.tfevents.1712414858.a39577a7e444.25850.4
- Xet hash:
- fa0462c39d6ff85ceacaa58da2a6cfc29323126d03fe0da450456203cd69d2a0
- Size of remote file:
- 29.2 kB
- SHA256:
- 3c290a608bc6d41fbea8b7ccac77dbf46fae2ed368b119878d447cc1b9f601c6
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