Instructions to use ZafarLocAI/convnext_checkpoints_with_class_weight with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZafarLocAI/convnext_checkpoints_with_class_weight with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ZafarLocAI/convnext_checkpoints_with_class_weight") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("ZafarLocAI/convnext_checkpoints_with_class_weight") model = AutoModelForImageClassification.from_pretrained("ZafarLocAI/convnext_checkpoints_with_class_weight", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download best/training_args.bin from ZafarLocAI/convnext_checkpoints_with_class_weight: direct link, hf CLI and curl.
- Browser
- Download file 5.27 kB
-
https://huggingface.co/ZafarLocAI/convnext_checkpoints_with_class_weight/resolve/main/best/training_args.bin
- Command line
-
hf download hf://ZafarLocAI/convnext_checkpoints_with_class_weight/best/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ZafarLocAI/convnext_checkpoints_with_class_weight/resolve/main/best/training_args.bin
5.27 kB
- Xet hash:
- 19e34c13c23fdb905937b4e84570dedf747cd12988fcf46728d72542d99a28c7
- Size of remote file:
- 5.27 kB
- SHA256:
- b66d2ea3755baff99bc42bbdfa40d2bbf5d1b0176acf1c8b69542822a0bcf49d
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