Instructions to use hf-internal-testing/tiny-random-layoutlmv2-for-dqa-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-layoutlmv2-for-dqa-test 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-layoutlmv2-for-dqa-test")# Load model directly from transformers import AutoProcessor, AutoModelForDocumentQuestionAnswering processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-layoutlmv2-for-dqa-test") model = AutoModelForDocumentQuestionAnswering.from_pretrained("hf-internal-testing/tiny-random-layoutlmv2-for-dqa-test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9a680171f4ebbb291ae98850c127c9734f706f76107f381bd0c19965eeb664b0
- Size of remote file:
- 374 MB
- SHA256:
- f6536743cf90e9e5b10047ef8e2a80d6a503ace699ac4bfb646ba47d6ed3be7c
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