Token Classification
Transformers
Safetensors
English
layoutlmv3
document-ai
invoice
sroie
BIO-tagging
NER
named-entity-recognition
multimodel
Instructions to use devashish-pisal/layoutlmv3-sroie-token-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devashish-pisal/layoutlmv3-sroie-token-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="devashish-pisal/layoutlmv3-sroie-token-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("devashish-pisal/layoutlmv3-sroie-token-classification") model = AutoModelForTokenClassification.from_pretrained("devashish-pisal/layoutlmv3-sroie-token-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from devashish-pisal/layoutlmv3-sroie-token-classification: direct link, hf CLI and curl.
- Browser
- Download file 501 MB
-
https://huggingface.co/devashish-pisal/layoutlmv3-sroie-token-classification/resolve/main/model.safetensors
- Command line
-
hf download hf://devashish-pisal/layoutlmv3-sroie-token-classification/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/devashish-pisal/layoutlmv3-sroie-token-classification/resolve/main/model.safetensors
501 MB
- Xet hash:
- b28eb4225f3dee6d6b52dc2e68c25ae222c40fda65a63350d7a29e184044aa70
- Size of remote file:
- 501 MB
- SHA256:
- ee3a4ed8ff31fd0695c75a98f3fbd58e433268226ab08742d3d89f4b787c4827
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