Instructions to use BTX24/deit-base-patch16-224-finetuned-stroke-binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BTX24/deit-base-patch16-224-finetuned-stroke-binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="BTX24/deit-base-patch16-224-finetuned-stroke-binary") 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("BTX24/deit-base-patch16-224-finetuned-stroke-binary") model = AutoModelForImageClassification.from_pretrained("BTX24/deit-base-patch16-224-finetuned-stroke-binary", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 900
Browse files
model.safetensors
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runs/Mar16_19-32-23_774ccf98b3fe/events.out.tfevents.1742156353.774ccf98b3fe.5066.28
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