Instructions to use hf-tiny-model-private/tiny-random-LayoutLMForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-LayoutLMForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="hf-tiny-model-private/tiny-random-LayoutLMForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForDocumentQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-LayoutLMForQuestionAnswering") model = AutoModelForDocumentQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-LayoutLMForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 67843fecd3f45a659c760b3c59a49d313691ce944b284ff020a5b0623ab27535
- Size of remote file:
- 1.01 MB
- SHA256:
- f1764b7a2f216e52a53f7f780cc2c98226f3a9549b55e784068bdb623ed53ff6
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