GLTR: Giant Language Model Test Room
Detecting text that was generated from large language models (e.g. GPT-2).
webpage: http://gltr.io
online-demo: http://gltr.io/dist/index.html
paper: https://arxiv.org/abs/1906.04043
A project by Hendrik Strobelt, Sebastian Gehrmann, Alexander M. Rush.
collaboration of MIT-IBM Watson AI Lab and HarvardNLP
Quickstart
Install dependencies for Python >3.6 :
pip install -r requirements.txtrun server for gpt-2-small:
python server.py
the demo instance runs now at http://localhost:5001/client/index.html
Run the BERT server
start the server for BERT:
python server.py --model BERTthe instance runs now at http://localhost:5001/client/index.html?nodemo. HINT: we only provide demo texts for gpt2-small.
server.py options
usage: server.py [-h] [--model MODEL] [--nodebug NODEBUG] [--address ADDRESS]
[--port PORT] [--nocache NOCACHE] [--dir DIR] [--no_cors]
optional arguments:
-h, --help show this help message and exit
--model MODEL choose either 'gpt-2-small' (default) or 'BERT' or your own
--nodebug NODEBUG server in non-debugging mode
--port PORT port to launch UI and API (default:5001)
--no_cors launch API without CORS support (default: False)
Extend backend
The backend defines a number of model api's that can be invoked by the server by starting it with the parameter --model NAME. To add a custom model, you need to write your own api in backend/api.py and add the decorator @register_api(name=NAME).
Each api needs to be a class that inherits from AbstractLanguageChecker, which defines two functions check_probabilities and postprocess. Please follow the documentation within api.py when implementing the class and the functions.
Extend frontend
the source code for the front-end is in client/src.
To modify, installing of node dependencies is necessary:
cd client/src; npm install; cd ../..re-compilation of front-end:
> rm -rf client/dist;cd client/src/; npm run build; cd ../..License
Apache 2
(c) 2019 by Hendrik Strobelt, Sebastian Gehrmann, Alexander M. Rush