Transfer learning for NLP models by annotating your textual data
Label Studio for Transformers
Transfer learning for NLP models by annotating your textual data without any additional coding.
This package provides a ready-to-use container that links together:
Quick Usage
Install Label Studio and other dependencies
pip install -r requirements.txt
Create ML backend with BERT classifier
label-studio-ml init my-ml-backend --script models/bert_classifier.py
cp models/utils.py my-ml-backend/utils.py
Create ML backend with BERT named entity recognizer
label-studio-ml init my-ml-backend --script models/ner.py
cp models/utils.py my-ml-backend/utils.py
Start ML backend at http://localhost:9090
label-studio-ml start my-ml-backend
Start Label Studio with ML backend connection
label-studio start my-annotation-project --init --ml-backend http://localhost:9090
The browser opens at http://localhost:8080. Upload your data on Import page then annotate by selecting Labeling page.
Once you’ve annotate