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:
- 5bce61dd4615d359a2ee7115c86425b2ed6cb00a0fc8dec0898d909cca8f2af8
- Size of remote file:
- 891 kB
- SHA256:
- 31f01e119265fc25efcfb04c0a9df617e3c4241b92d0312f4f327b0c0c83392f
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