Show HN: I made a free-to-use GPT-2 API
booste.io
booste.io
The goal is simplicity, so you hit the endpoint with a one-line call from the Python client.
Here's a demo of pip install, code, and use. https://www.loom.com/share/c09c9ca228644345852544808decd864
This API is the first API from https://www.booste.io, where my mission is to make the ML stack as simple as Stripe made the payments stack. One-line API clients.
Lots on the roadmap (Node client, using larger GPT-2 model, PPLM for long-content generation, running on GPUs, hosting other models such as BERT), but there's no time like the present to put something out there.
Let me know your thoughts :)
(edit: fixed link)
Found a memory leak. Luckily it self heals on crash, so downtime is minimal. You can expect this api to be live 55/60 minutes. Will be fixing tomorrow - for now, it's bedtime.
If you want to wait for something with guaranteed uptime, jump on the waitlist at https://www.booste.io and I'll be reaching out when appropriate.
https://bellard.org/nncp/gpt2tc.html
I tried it using a GPT-2 model I'd finetuned, and it worked well.
I started making a simple chatbot with it using Python: at each step, I fed in the conversation so far, and a speaker prompt (e.g. PERSON2:), and read the output until I saw PERSON1: appear. Rinse and repeat.
Unfortunately, I got stuck with some text encoding issue between python and the CLI binary. I tried obvious things like forcing the decode to use UTF-8, but after a couple of steps I always ended up receiving some characters that weren't valid.
I didn't have this problem when running the binary from the command line, so it must have been something to do with how I was using python popen.
It says on the website "Predict the next word(s) from a given sequence of words." Speaking as someone who has very little programming knowledge, would it be possible to use this to create a gmail like auto-complete with this? If so, how can I make it so that the words generated resemble my own writing style (like gmail auto-complete does?).
Other APIs I launch in the future should help. BERT comes to mind. You could generate multiple options using GPT2, then have BERT assess if they're in your style.
For CV, it's not on the near roadmap. I've looked into hosting OpenPose and YoloV3. OpenPose could work for a fitness project but Yolo definitely needs custom training to be novel. In the future with this project I plan to do custom training as well, which would make using novel CV models a possibility. For now, the plan is to stay focused on NLP since pretrained models can handle a broader range of novel use cases.
I have a form on the docs site (and here: https://forms.gle/yoENXh4tLU5cTW2P8) for requesting new models, so down the line I know who to be talking to and which models to prioritize.
Add-ons such as style transfer logic or any form of personalization on the model would have a cost, haven't done the math yet so I couldn't reasonably ballpark it.