This is a much easier way to run the model. I'm going to update the huggingface README to point to this. The one thing that could be improved is the turn-taking between user and assistant, which it sometimes gets confused about. I fixed that in my fork of your gist here: https://gist.github.com/samdobson/975c8b095a71bbdf1488987eac...
I didn't get as good results as Karpathy (unlucky seed?)
It's fun to play with though...
User: How many legs does a dog have?
Assistant: That's a great question that has been debated by dog enthusiasts for centuries. There's no one "right" answer (...)
There's not much to it... it took longer to spin up the cloud machine than it did to kick off the training run. I'll be writing up a blog post with a step-by-step guide when I get a free moment, but in the meantime, here are the commands I ran: https://pastebin.com/sdKVy0NR
This one is mine. It's a light-hearted digital newspaper of sorts, covering news from local British communities through the medium of verse (generated by LLMs).
Until now I've been using ChatGPT for the generation, with a fairly generic prompt that asks for a poem about the article that follows. ChatGPT's ability to summarise is incredible. It's really not great, though, at rhyme and meter. That means a decent amount of curation and heavy editing is needed for the best to get something passable. Prompt engineering has not seemed to have a meaningful impact. I'm looking to fine-tune a davinci model, which I think will deliver higher quality with less effort.
The quality can mostly be blamed on me, rather than GPT-3. I haven't written a poem since school :)
The accompanying illustrations are created with Stable Diffusion using DiffusionBee. Images take around 30s to generate on my Macbook Air M1. I'm looking to switch to MochiDiffusion to cut generation time a bit.
The blog is running Ghost on a small DigitalOcean VPS, with emails delivered by Mailgun.
The process right now is somewhat labour-intensive: between researching news stories, iterating on the content, and publishing, it takes a decent amount of time for each piece of content. I'm confident in being able to automate a large part of it, in time.
One fun fact I learned when planning the virtual road-trip for this project: in average traffic conditions, it's possible to visit every city in England in less than 48 hours. The near-optimum solution to this formulation of the Traveling Salesmen Problem (starting in the South West), a route taking 47:00:10, was calculated in less than 5 seconds with a Guided Local Search algorithm. [1]
Technology means that I can virtually, learn about, write creatively, and publish regularly, all whilst having a family and a full-time job. What a time to be alive!
Very open to your thoughts, and indeed to feedback on the concept or the execution.
For short-term career growth, $YOUR_COMPANY's current preferred ETL tool will have the biggest ROI. Focus on design patterns: while APIs will come and go, the concepts, as you rightly say, are transferrable.
If you're looking to land a new role: the market says dbt, databricks and snowflake are pretty strong bets.
If it's personal interest, or a high-risk, high-reward long term play, take your pick from any of the new hotness!
A stark reminder to end users of any service that if you are not paying, you are the product. There is good reason that the sale of financial services through intermediaries is a highly regulated area: it takes a firm counter-force to stop businesses from exploiting customers when all the incentives are there, and there are enough links in the chain for plausible deniability.