Instructions to use karim155/convnext-tiny-224-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karim155/convnext-tiny-224-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="karim155/convnext-tiny-224-finetuned") 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("karim155/convnext-tiny-224-finetuned") model = AutoModelForImageClassification.from_pretrained("karim155/convnext-tiny-224-finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
convnext-tiny-224-finetuned / runs /Aug19_10-42-47_6801bce4c4b3 /events.out.tfevents.1724064200.6801bce4c4b3.1808.0
- Xet hash:
- 66cb978bf0516b5a15c41706d06469f947a94b8a8528e1765dd1042ad4c3b8f0
- Size of remote file:
- 6.41 kB
- SHA256:
- d2cbde9f15c13678bc1da8edc3a6e7efa85391a621a0e6beac57d3020c883bbf
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