Instructions to use crystalchen/layoutlm-funsd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use crystalchen/layoutlm-funsd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="crystalchen/layoutlm-funsd")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("crystalchen/layoutlm-funsd") model = AutoModelForTokenClassification.from_pretrained("crystalchen/layoutlm-funsd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d5d50ffba764ed53545797fb8509778fd5f4eac63ae19df3607f5cc2c8c6def1
- Size of remote file:
- 5.3 kB
- SHA256:
- 9378062de1d4aa3a1525d8279ebd4e5a21e9cf7015c97f77db495e0b8682b50c
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