Object Detection
Transformers
PyTorch
TensorBoard
layoutlmv3
token-classification
Generated from Trainer
Eval Results (legacy)
Instructions to use Narsil/layoutlmv3-finetuned-funsd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Narsil/layoutlmv3-finetuned-funsd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="Narsil/layoutlmv3-finetuned-funsd")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("Narsil/layoutlmv3-finetuned-funsd") model = AutoModelForTokenClassification.from_pretrained("Narsil/layoutlmv3-finetuned-funsd") - Notebooks
- Google Colab
- Kaggle
| { | |
| "apply_ocr": true, | |
| "do_normalize": true, | |
| "do_resize": true, | |
| "feature_extractor_type": "LayoutLMv3FeatureExtractor", | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "ocr_lang": null, | |
| "resample": 2, | |
| "size": 224 | |
| } |