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") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_valid_processor_keys": [ | |
| "images", | |
| "do_resize", | |
| "size", | |
| "resample", | |
| "apply_ocr", | |
| "ocr_lang", | |
| "tesseract_config", | |
| "return_tensors", | |
| "data_format", | |
| "input_data_format" | |
| ], | |
| "apply_ocr": true, | |
| "do_resize": true, | |
| "image_processor_type": "LayoutLMv2ImageProcessor", | |
| "ocr_lang": null, | |
| "resample": 2, | |
| "size": { | |
| "height": 224, | |
| "width": 224 | |
| }, | |
| "tesseract_config": "" | |
| } | |