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")# 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
- Xet hash:
- 7a4877ae220357966fc83536d7d055a61d15b47d2a4d6da806bc2612a865a2e8
- Size of remote file:
- 343 MB
- SHA256:
- 83928cef548c01069d7ccdac9276a369ba934e364667133ddb531589b1d85417
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