Instructions to use Waleed-bin-Qamar/ConvNext-For-Covid-Classification-30EP-BS64 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Waleed-bin-Qamar/ConvNext-For-Covid-Classification-30EP-BS64 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Waleed-bin-Qamar/ConvNext-For-Covid-Classification-30EP-BS64") 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("Waleed-bin-Qamar/ConvNext-For-Covid-Classification-30EP-BS64") model = AutoModelForImageClassification.from_pretrained("Waleed-bin-Qamar/ConvNext-For-Covid-Classification-30EP-BS64") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 59136b05cb863af3c960991ef136a6fbe1efac48ac2c958ddce34aa198e50023
- Size of remote file:
- 111 MB
- SHA256:
- 18c07728bf25f5cca3dc44d73806d655c8e10473b9e42b87320d21e92832375f
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