Instructions to use daniyalumerr/LayoutLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use daniyalumerr/LayoutLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="daniyalumerr/LayoutLM")# Load model directly from transformers import AutoTokenizer, AutoModelForDocumentQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("daniyalumerr/LayoutLM") model = AutoModelForDocumentQuestionAnswering.from_pretrained("daniyalumerr/LayoutLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ede7d942397873a8ce94eb565a3b1e8310984232076bb7cc4a4bce82164a73cc
- Size of remote file:
- 511 MB
- SHA256:
- e4bbad3e4a1b5ae50c787b7afd6049a0bfa99fd823b50436e444e092ae2347b9
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