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:
- 0c344dcb7b955f87df54f354a3a49d694790c1284186fe0821b5deba6375e030
- Size of remote file:
- 59.9 MB
- SHA256:
- 4ffff54193e685a4e2df2da5d9550d5f234daa8bea3e882b0bdd7e00c29a0e77
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