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:
- a39b9b96add8d1336f6a605c0eab88b2a4f591b660b2e3f134fd94dd7d7064c7
- Size of remote file:
- 1.01 MB
- SHA256:
- 5296cbc0e03f8a5cf90c90381d3911054dbd8f48e399e57a1e22e088f26fb1b8
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