Instructions to use vatipham/layoutlm-funsd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vatipham/layoutlm-funsd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="vatipham/layoutlm-funsd")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("vatipham/layoutlm-funsd") model = AutoModelForTokenClassification.from_pretrained("vatipham/layoutlm-funsd", device_map="auto") - 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:e3b6cac909d36117a83176995e01d426449f24b58b6e81c66f9f9c1ad1d05d57
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size 450558212
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