Instructions to use EdBergJr/layoutlm-funsd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EdBergJr/layoutlm-funsd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="EdBergJr/layoutlm-funsd")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("EdBergJr/layoutlm-funsd") model = AutoModelForTokenClassification.from_pretrained("EdBergJr/layoutlm-funsd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8ccc36d0a19cc23928283df01d6253fa87b11952522a42f055534cc17ad51ee3
- Size of remote file:
- 5.84 kB
- SHA256:
- 92997b80b4f5e1e39c24b9d54f3465a9c121d40f5158eb589872a0bd2854a347
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