Instructions to use hf-internal-testing/tiny-random-MarkupLMForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MarkupLMForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hf-internal-testing/tiny-random-MarkupLMForQuestionAnswering")# Load model directly from transformers import AutoProcessor, AutoModelForQuestionAnswering processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-MarkupLMForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-internal-testing/tiny-random-MarkupLMForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b8d89bbe18e5ecadc0f4f67c2a9ff1921f9c640bc94fe1e4e402351921292bb0
- Size of remote file:
- 6.94 MB
- SHA256:
- 8c33d3ee5d0c512d15e56d1dff71ac389bbdf6db8268c3114682493fc72dd27e
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