Instructions to use manudeva/intervUone with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use manudeva/intervUone with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="manudeva/intervUone") 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("manudeva/intervUone") model = AutoModelForImageClassification.from_pretrained("manudeva/intervUone") - Notebooks
- Google Colab
- Kaggle
intervUone
Autogenerated by HuggingPics🤗🖼️
Create your own image classifier for anything by running the demo on Google Colab.
Report any issues with the demo at the github repo.
Example Images
person sitting in chair leaning back
person sitting leaning left in chair
person sitting leaning right in chair
person sitting upright in chair
person slouching in chair
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Evaluation results
- Accuracyself-reported0.175




