You can deploy this model and start earning money today!

nlpso/
m1_ind_layers_ocr_cmbert_iob2_level_1

Name: m1_ind_layers_ocr_cmbert_iob2_level_1
Availability: InStock

nlpso/m1_fine_tuning_ocr_cmbert_iob2

autotrain_compatible

endpoints_compatible

Views

No views yet

m1_ind_layers_ocr_cmbert_iob2_level_1

Introduction

This model is a model that was fine-tuned from Jean-Baptiste/camembert-ner 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 : Jean-Baptiste/camembert-ner
Dataset : noisy (Pero OCR)
Tagging format : IOB2
Recognised entities : level 1

Load model from the Hugging Face

**Warning 1 ** : this model only recognises level-1 entities of dataset. It has to be used with m1_ind_layers_ocr_cmbert_iob2_level_2 to recognise nested entities level-2.

python

from transformers import AutoTokenizer, AutoModelForTokenClassification

tokenizer = AutoTokenizer.from_pretrained("nlpso/m1_ind_layers_ocr_cmbert_iob2_level_1")
model = AutoModelForTokenClassification.from_pretrained("nlpso/m1_ind_layers_ocr_cmbert_iob2_level_1")