Instructions to use hf-internal-testing/tiny-random-LayoutLMForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-LayoutLMForQuestionAnswering 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-LayoutLMForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForDocumentQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-LayoutLMForQuestionAnswering") model = AutoModelForDocumentQuestionAnswering.from_pretrained("hf-internal-testing/tiny-random-LayoutLMForQuestionAnswering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 686bea6eceab2ce83b88f9c34a51bd0919205490330f858c1308434b3db1a923
- Size of remote file:
- 911 kB
- SHA256:
- a0d023aa70c11777330baf1da3c4bb212f283a9028d14723fa222d23cbb78206
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