Instructions to use omarelsayeed/LayoutReader73 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use omarelsayeed/LayoutReader73 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="omarelsayeed/LayoutReader73")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("omarelsayeed/LayoutReader73") model = AutoModelForTokenClassification.from_pretrained("omarelsayeed/LayoutReader73") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b7ba982c6be1c391f2b7540ec250476a03e2cf621c87a5734e25c502fb59f673
- Size of remote file:
- 1.42 GB
- SHA256:
- 636e5d4a0030c8bd896b3fc4d4dba0d116dc336beba68ef5d867d88230a206f8
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