Instructions to use ZafarLocAI/convnext_checkpoints_mar20_classification_combat_mission with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZafarLocAI/convnext_checkpoints_mar20_classification_combat_mission with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ZafarLocAI/convnext_checkpoints_mar20_classification_combat_mission") 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_mar20_classification_combat_mission") model = AutoModelForImageClassification.from_pretrained("ZafarLocAI/convnext_checkpoints_mar20_classification_combat_mission", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f9e69c7d5fccb7f6d2207605909833bc3b1e7ad3f18d69a3a934e6876b3d3019
- Size of remote file:
- 786 MB
- SHA256:
- 9e5609dfff791ac63051efefe5ef7a4d309c7ddacdae86255b1c2d1d0e241e1d
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