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ACCORD-NLP/
ner-roberta-large-lm

Name: ner-roberta-large-lm
Availability: InStock

ACCORD-NLP/CODE-ACCORD-Entities

apache-2.0

autotrain_compatible

endpoints_compatible

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ACCORD-NLP

ACCORD-NLP is a Natural Language Processing (NLP) framework developed by the ACCORD project to facilitate Automated Compliance Checking (ACC) within the Architecture, Engineering, and Construction (AEC) sector. It consists of several pre-trained/fine-tuned machine learning models to perform the following information extraction tasks from regulatory text.

Entity Extraction/Classification (ner)
Relation Extraction/Classification (re)

ner-roberta-large-lm is a RoBERTa large model fine-tuned for sequence labelling/entity classification using CODE-ACCORD entities dataset, following language modelling using a building regulatory text corpus.

Installation

From Source

git clone https://github.com/Accord-Project/accord-nlp.git
cd accord-nlp
pip install -r requirements.txt

From pip

pip install accord-nlp

Using Pre-trained Models

Entity Extraction/Classification (ner)

python

from accord_nlp.text_classification.ner.ner_model import NERModel

model = NERModel('roberta', 'ACCORD-NLP/ner-roberta-large')
predictions, raw_outputs = model.predict(['The gradient of the passageway should not exceed five per cent.'])
print(predictions)

Relation Extraction/Classification (re)