# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("welcomyou/layoutlmv3-vn-admin-kie", dtype="auto")LayoutLMv3 — Vietnamese administrative document KIE
Fine-tuned microsoft/layoutlmv3-base for key-information extraction on Vietnamese administrative documents (Quyết định, Công văn, Tờ trình, Báo cáo, ...).
The variant is the fontgray-norm flavour: token_type_ids encode three style buckets derived from per-word font size, foreground gray level, and word height (see style_emphasis_ids in the training pipeline).
Files
layoutlmv3_fontgray_norm_final_epoch25/layoutlmv3_fontgray_norm_final_epoch25.int8.onnx— quantized INT8 ONNX modellayoutlmv3_fontgray_norm_final_epoch25/label_list.json— label vocabulary (BIO tags)layoutlmv3_fontgray_norm_final_epoch25/layoutlmv3_fontgray_config.json— runtime config (style buckets, line position buckets)- Tokenizer files (
tokenizer.json,tokenizer_config.json,special_tokens_map.json,vocab.txt, …)
Intended use
This model is designed for the ScanIndex pipeline. It expects the canonical OCR JSON profile produced by ScreenAI + the project's preprocessing (layoutlmv3_runtime_v1). Using it standalone requires reproducing that input format.
Loading
from huggingface_hub import snapshot_download
local = snapshot_download("welcomyou/layoutlmv3-vn-admin-kie", local_dir="models")
# Then point ScanIndex at <repo>/models/layoutlmv3_fontgray_norm_final_epoch25/
Training & data
See train-convert/kie/train_kie/layoutlmv3_fontgray_norm/ for the training scripts and decision records.
Trained on internal annotated Vietnamese admin documents (not redistributed).
License
Inherits LayoutLMv3 base license: CC-BY-NC-SA-4.0 (research / non-commercial). Commercial use requires a separate agreement with Microsoft for the base model.
Model tree for welcomyou/layoutlmv3-vn-admin-kie
Base model
microsoft/layoutlmv3-base
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="welcomyou/layoutlmv3-vn-admin-kie")