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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 89d05f7f8b25d6ef1c28dc30c3b6845883dd60e2aeb55fd4b034fb3111d41815
- Size of remote file:
- 110 MB
- SHA256:
- bd5c9de5c03586a4f4159884130e578da024a10c7f685ae7cdd8dfd343f97b03
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