Instructions to use PrplHrt/LayoutLMv2_hub_500 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PrplHrt/LayoutLMv2_hub_500 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="PrplHrt/LayoutLMv2_hub_500")# Load model directly from transformers import AutoProcessor, AutoModelForDocumentQuestionAnswering processor = AutoProcessor.from_pretrained("PrplHrt/LayoutLMv2_hub_500") model = AutoModelForDocumentQuestionAnswering.from_pretrained("PrplHrt/LayoutLMv2_hub_500", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b60cfc4160461b66a341a10fd972fd141454ded6197015b7e70b34b2eae8a6e4
- Size of remote file:
- 802 MB
- SHA256:
- 379b47581b36b9f8e3b69129d701ef8d6ca54a5bed97337127314336ca44bdd1
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