Instructions to use renjithks/layoutlmv3-er-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use renjithks/layoutlmv3-er-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="renjithks/layoutlmv3-er-ner")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("renjithks/layoutlmv3-er-ner") model = AutoModelForTokenClassification.from_pretrained("renjithks/layoutlmv3-er-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d4ef9ae5945df8e95a01be079d9bf2ed8c0eb57e8fac57f2a7aace65f8e7495b
- Size of remote file:
- 501 MB
- SHA256:
- c6e0de73fc383ef6244d512f1ac2cbaa3d15e05e865db12b07644314b5a9a1e2
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