Instructions to use hf-internal-testing/tiny-random-LayoutLMv3ForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-LayoutLMv3ForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="hf-internal-testing/tiny-random-LayoutLMv3ForQuestionAnswering")# Load model directly from transformers import AutoProcessor, AutoModelForDocumentQuestionAnswering processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-LayoutLMv3ForQuestionAnswering") model = AutoModelForDocumentQuestionAnswering.from_pretrained("hf-internal-testing/tiny-random-LayoutLMv3ForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd6e886f03194a384e0c40d9ad49b4ba6876aac3c2e6cf3217a3a2415d511c3f
- Size of remote file:
- 459 kB
- SHA256:
- bf21de3fc684f61c4cafa6cb1f27728ce55e42a91c67e28f1c1ff6078ea84688
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