pierreguillou/DocLayNet-large
Updated • 295 • 14
How to use Kwan0/layoutlmv3-base-finetune-DocLayNet-100k with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("token-classification", model="Kwan0/layoutlmv3-base-finetune-DocLayNet-100k") # Load model directly
from transformers import AutoProcessor, AutoModelForTokenClassification
processor = AutoProcessor.from_pretrained("Kwan0/layoutlmv3-base-finetune-DocLayNet-100k")
model = AutoModelForTokenClassification.from_pretrained("Kwan0/layoutlmv3-base-finetune-DocLayNet-100k")This model is a fine-tuned version of microsoft/layoutlmv3-base on the pierreguillou/DocLayNet-large using bounding boxes and categories for lines (not for for paragraphs). It achieves the following results on the evaluation set:
The script for training can be found here: https://github.com/huggingface/transformers/tree/main/examples/research_projects/layoutlmv3
More information needed
The following hyperparameters were used during training:
Base model
microsoft/layoutlmv3-base