Instructions to use rushda7/layoutlm-funsd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rushda7/layoutlm-funsd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="rushda7/layoutlm-funsd")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("rushda7/layoutlm-funsd") model = AutoModelForTokenClassification.from_pretrained("rushda7/layoutlm-funsd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 76bbcce60f1b2094d6192b81d8a3816a1eeddef0a0d2cf176c3704dda1100768
- Size of remote file:
- 451 MB
- SHA256:
- 941e539cca7b14f196fea900c869dc1b6716e692db31651cf80108a39b115a0c
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