Instructions to use Jagannath/handwritingDetection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jagannath/handwritingDetection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Jagannath/handwritingDetection") 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("Jagannath/handwritingDetection") model = AutoModelForImageClassification.from_pretrained("Jagannath/handwritingDetection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#2)
- Adding `safetensors` variant of this model (79cbb2b4374be8a6e8adebdbcd9dbbfc28c98ee0) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>c5c95b2 -
Upload . with huggingface_hub (#1)
- Upload . with huggingface_hub (e562b6a3df626e9b2a9c8a9b7fd6c42864b8b5ef)9c5f783
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initial commit
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