Instructions to use Prot10/convnextv2-base-1k-224-for-pre_evaluation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Prot10/convnextv2-base-1k-224-for-pre_evaluation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Prot10/convnextv2-base-1k-224-for-pre_evaluation") 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("Prot10/convnextv2-base-1k-224-for-pre_evaluation") model = AutoModelForImageClassification.from_pretrained("Prot10/convnextv2-base-1k-224-for-pre_evaluation") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13788ac36b5ae4ea13175b13e50d14d5aee885e9954dc7f5c91d54f8e5e41312
- Size of remote file:
- 4.09 kB
- SHA256:
- 462bd140bcf73ab7d2dd67c846c7fc28a2f15ba548bf01de871909e41de1df25
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