Detecting text that was generated from large language models (e.g. GPT-2).
![](https://raw.githubusercontent.com/ariafyy/detecting-fake-text/master/figs/overview.png)
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
Install dependencies for Python >3.6 :
pip install -r requirements.txt
run server for gpt-2-small
:
python server.py
the demo instance runs now at http://localhost:5001/client/index.html
start the server for BERT
:
python server.py --model BERT
the instance runs now at http://localhost:5001/client/index.html?nodemo. HINT: we only provide demo texts for gpt2-small
.
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)
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.
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 ../..
Apache 2
(c) 2019 by Hendrik Strobelt, Sebastian Gehrmann, Alexander M. Rush