Instructions to use ImageIN/convnext-base-224_finetuned_on_ImageIn_annotations with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ImageIN/convnext-base-224_finetuned_on_ImageIn_annotations with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ImageIN/convnext-base-224_finetuned_on_ImageIn_annotations") 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("ImageIN/convnext-base-224_finetuned_on_ImageIn_annotations") model = AutoModelForImageClassification.from_pretrained("ImageIN/convnext-base-224_finetuned_on_ImageIn_annotations", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (c855cc8e05b2153c3b1cf80571d90398f4d005aa) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>161c5b6
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update model card README.md
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training finished
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Training in progress, epoch 1
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initial commit
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