Instructions to use brandaobrandisborges/layoutlm-synthchecking with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use brandaobrandisborges/layoutlm-synthchecking with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="brandaobrandisborges/layoutlm-synthchecking")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("brandaobrandisborges/layoutlm-synthchecking") model = AutoModelForTokenClassification.from_pretrained("brandaobrandisborges/layoutlm-synthchecking") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4251d59f3dd61b863af7fad79a79dac501d16cd7c5ba2536c4ebe62f4f71dd3c
- Size of remote file:
- 3.58 kB
- SHA256:
- 0e9736fd9fe5af28eedb33462d7cadbb12e279de257edd78014e053d4c7ed88e
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