Instructions to use TusharGoel/LayoutLMv2-finetuned-docvqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TusharGoel/LayoutLMv2-finetuned-docvqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="TusharGoel/LayoutLMv2-finetuned-docvqa")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForDocumentQuestionAnswering processor = AutoProcessor.from_pretrained("TusharGoel/LayoutLMv2-finetuned-docvqa") model = AutoModelForDocumentQuestionAnswering.from_pretrained("TusharGoel/LayoutLMv2-finetuned-docvqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from TusharGoel/LayoutLMv2-finetuned-docvqa: direct link, hf CLI and curl.
- Browser
- Download file 136 Bytes
-
https://huggingface.co/TusharGoel/LayoutLMv2-finetuned-docvqa/resolve/refs%2Fpr%2F1/preprocessor_config.json
- Command line
-
hf download hf://TusharGoel/LayoutLMv2-finetuned-docvqa@refs/pr/1/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/TusharGoel/LayoutLMv2-finetuned-docvqa/resolve/refs%2Fpr%2F1/preprocessor_config.json
136 Bytes
| { | |
| "apply_ocr": false, | |
| "do_resize": true, | |
| "feature_extractor_type": "LayoutLMv2FeatureExtractor", | |
| "resample": 2, | |
| "size": 224 | |
| } | |