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m1_ind_layers_ocr_cmbert_io_level_2
nlpso/m1_ind_layers_ocr_cmbert_io_level_2
m1_ind_layers_ocr_cmbert_io_level_2 is a token classification model from nlpso. Use it when you need labels on individual words, such as names. It is set up for transformers.
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.
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At a glance
- Task
- Token Classification
- Library
- transformers
- Model type
- camembert
- Access
- Public
- Created
- Feb 9, 2023
- Updated
- Feb 16, 2023
- SHA
- ddcf27d9
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Model card
From the Hugging Face model README
m1_ind_layers_ocr_cmbert_io_level_2
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 : IO
- Recognised entities : level 2
Load model from the Hugging Face
**Warning 1 ** : this model only recognises level-2 entities of dataset. It has to be used with m1_ind_layers_ocr_cmbert_io_level_1 to recognise nested entities level-1.
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("nlpso/m1_ind_layers_ocr_cmbert_io_level_2")
model = AutoModelForTokenClassification.from_pretrained("nlpso/m1_ind_layers_ocr_cmbert_io_level_2")
- Task
- Token Classification
- Library
- transformers
- Type
- camembert
- Languages
- fr
- Created
- Feb 9, 2023
- Updated
- Feb 16, 2023