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:
- 2cfcfcc9894cdf1b1a4cab197e096db0217037e179bbc33d88c782a2b45fe7c5
- Size of remote file:
- 7.14 kB
- SHA256:
- dce8c6e43d4505cb656b6f2376159760ab64b06cde0bc4e5a9ca19c5bc921bc7
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