m2_joint_label_ocr_ptrn_cmbert_io

Introduction

This model is a fine-tuned verion from HueyNemud/das22-10-camembert_pretrained for nested NER task on a nested NER Paris trade directories dataset.

Dataset

Abbreviation	Entity group (level)	Description
O	1 & 2	Outside of a named entity
PER	1	Person or company name
ACT	1 & 2	Person or company professional activity
TITREH	2	Military or civil distinction
DESC	1	Entry full description
TITREP	2	Professionnal reward
SPAT	1	Address
LOC	2	Street name
CARDINAL	2	Street number
FT	2	Geographical feature

Experiment parameter

• Pretrained-model : HueyNemud/das22-10-camembert_pretrained
• Dataset : noisy (Pero OCR)
• Tagging format : IO
• Recognised entities : 'All'

Load model from the Hugging Face

from transformers import AutoTokenizer, AutoModelForTokenClassification

tokenizer = AutoTokenizer.from_pretrained("nlpso/m2_joint_label_ocr_ptrn_cmbert_io")
model = AutoModelForTokenClassification.from_pretrained("nlpso/m2_joint_label_ocr_ptrn_cmbert_io")