Instructions to use ZafarLocAI/convnext_checkpoints_plane_noplane_25_march with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZafarLocAI/convnext_checkpoints_plane_noplane_25_march with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ZafarLocAI/convnext_checkpoints_plane_noplane_25_march") 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("ZafarLocAI/convnext_checkpoints_plane_noplane_25_march") model = AutoModelForImageClassification.from_pretrained("ZafarLocAI/convnext_checkpoints_plane_noplane_25_march", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 34e069267f0ed14ffd70d44e4b770949e07be774500d4829d2e6d35ac140083f
- Size of remote file:
- 5.27 kB
- SHA256:
- 31314a392ea476bbe2fad70bed2108e004ffe3e8419af0f7a998f277fcd3c1b2
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