gpt-j-api

An API to interact with the GPT-J language model. You can use and test the model in two different ways:

Streamlit web app at http://api.vicgalle.net:8000/
The proper API, documented at http://api.vicgalle.net:5000/docs

Using the API

  • Python:
import requests
context = "In a shocking finding, scientist discovered a herd of unicorns living in a remote, previously unexplored valley, in the Andes Mountains. Even more surprising to the researchers was the fact that the unicorns spoke perfect English."
payload = {
    "context": context,
    "token_max_length": 512,
    "temperature": 1.0,
    "top_p": 0.9,
}
response = requests.post("http://api.vicgalle.net:5000/generate", params=payload).json()
print(response)
  • Bash:
curl -X 'POST' \
  'http://api.vicgalle.net:5000/generate?context=In%20a%20shocking%20finding%2C%20scientists%20discovered%20a%20herd%20of%20unicorns%20living%20in%20a%20remote%2C%20previously%20unexplored%20valley%2C%20in%20the%20Andes%20Mountains.%20Even%20more%20surprising%20to%20the%20researchers%20was%20the%20fact%20that%20the%20unicorns%20spoke%20perfect%20English.&token_max_length=512&temperature=1&top_p=0.9' \
  -H 'accept: application/json' \
  -d ''

Deployment of the API server

Just ssh into a TPU VM. This code was only tested on the v3-8 variants.

First, install the requirements and get the weigts:

python3 -m pip install -r requirements.txt
wget https://the-eye.eu/public/AI/GPT-J-6B/step_383500_slim.tar.zstd
sudo apt install zstd
tar -I zstd -xf step_383500_slim.tar.zstd

And just run

python3 serve.py

Then, you can go to http://localhost:5000/docs and use the API!

Deploy the streamlit dashboard

Just run

python3 -m streamlit run streamlit_app.py --server.port 8000

GitHub

https://github.com/vicgalle/gpt-j-api