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:
- e9f321b3205500de6070a900bc1d219d8899c48c905a617fee3f0b65f5c5b9b4
- Size of remote file:
- 444 kB
- SHA256:
- 3b5cfd24d806770263c0a1b97cf7a57211bf013356ee5c95401caafdbd49e5b5
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