Instructions to use hf-internal-testing/tiny-random-LayoutLMv2ForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-LayoutLMv2ForQuestionAnswering 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-LayoutLMv2ForQuestionAnswering")# Load model directly from transformers import AutoProcessor, AutoModelForDocumentQuestionAnswering processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-LayoutLMv2ForQuestionAnswering") model = AutoModelForDocumentQuestionAnswering.from_pretrained("hf-internal-testing/tiny-random-LayoutLMv2ForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6ae214f50a5561c1858ecddd54a43a2c1847cc2dcffaf674cfafc57a1b498b8d
- Size of remote file:
- 59.9 MB
- SHA256:
- f8c4bf5074740a1b79c72b156c23f9c3bdc9faa96a8243bb890c34b1ccff5e69
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