Instructions to use gagan3012/swin_arocr_tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gagan3012/swin_arocr_tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="gagan3012/swin_arocr_tiny")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("gagan3012/swin_arocr_tiny") model = AutoModel.from_pretrained("gagan3012/swin_arocr_tiny") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:9b75fd37616256cc5bd98db481ce776c875f52ab259cbf7f75c2600b37ca1f09
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size 110342128
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