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:
- d417b1dd948e4e46bc60daa1ecca8a49339e3cd4b29174c70df27a1546e8f212
- Size of remote file:
- 535 kB
- SHA256:
- bd088f0a475eb433462eded5d4d352c4f03ca7365b8d1427f77af70e6ec5b464
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