website
helpmecode
website | helpmecode | |
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3 | 1 | |
7 | 54 | |
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0.0 | 2.8 | |
over 2 years ago | 3 months ago | |
CSS | Python | |
- | GNU General Public License v3.0 only |
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website
- How do I get started with Jax on TPU VMs
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GPT-J “the open source cousin of GPT-3 everyone can use”
Your view here is entirely reasonable. It was my view before I ever heard about TFRC. I was every bit as skeptical.
That view is wrong. From https://github.com/shawwn/website/blob/master/jaxtpu.md :
> So we're talking about a group of people who are the polar opposite of any Google support experience you may have had.
> Ever struggle with GCP support? They took two weeks to resolve my problem. During the whole process, I vividly remember feeling like, "They don't quite seem to understand what I'm saying... I'm not sure whether to be worried."
> Ever experience TFRC support? I've been a member for almost two years. I just counted how many times they failed to come through for me: zero times. And as far as I can remember, it took less than 48 hours to resolve whatever issue I was facing.
> For a Google project, this was somewhere between "space aliens" and "narnia" on the Scale of Surprising Things.
[...]
> My goal here is to finally put to rest this feeling that everyone has. There's some kind of reluctance to apply to TFRC. People always end up asking stuff like this:
> "I'm just a university student, not an established researcher. Should I apply?"
> Yes!
> "I'm just here to play around a bit with TPUs. I don't have any idea what I'm doing, but I'll poke around a bit and see what's up. Should I apply?"
> Heck yeah!
> "I have a Serious Research Project in mind. I'd like to evaluate whether the Cloud TPU VM platform is sufficient for our team's research goals. Should I apply?"
> Absolutely. But whoever you are, you've probably applied by now. Because everyone is realizing that TFRC is how you accomplish your research goals.
I expect that if you apply, you'll get your activation email within a few hours. Of course, you better get in quick. My goal here was to cause a stampede. Right now, in my experience, you'll be up and running by tomorrow. But if ten thousand people show up from HN, I don't know if that will remain true. :)
I feel a bit bad to be talking at length at TFRC. But then I remembered that none of this is off-topic in the slightest. GPT-J was proof of everything above. No TFRC, no GPT-J. The whole reason that the world can enjoy GPT-J now is because anyone can show up and start doing as many effective things as you can possibly learn.
It was all thanks to TFRC, the Cloud TPU team, the JAX team, the XLA compiler team -- hundreds of people, who have all managed to gift us this amazing opportunity. Yes, they want to win the ML mindshare war. But they know the way to win it is to care deeply about helping you achieve every one of your research goals.
Think of it like a side hobby. Best part is, it's free. (Just watch out for the egress bandwidth, ha. Otherwise you'll be talking with GCP support for your $500 refund -- and yes, that's an unpleasant experience.)
helpmecode
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GPT-J “the open source cousin of GPT-3 everyone can use”
I made a none-gpt variant of this idea for fun after watching some breathless microsoft video about AI in VS code, which amounted to autocomplete sorted by popularity.
It is just a wrapper to howdoi with a sprinkle of extra logic to make it a bit more useful.
https://github.com/irthomasthomas/helpmecode
Rather than creating fake code that looks real, this gives you the S.O. code answers verbatim. So you know it is probably out of date or wrong. At least you cant delude yourself (if you don't know how to write a piece of code then how can you judge the code written by GPT?).
My tool is great for getting a quick reminder of syntax without needing to switch to a browser. I could improve it by adding metadata like the date of the answer and comments maybe.
What are some alternatives?
mesh-transformer-jax - Model parallel transformers in JAX and Haiku
interactive-coding-challenges - 120+ interactive Python coding interview challenges (algorithms and data structures). Includes Anki flashcards.
gpt-neo - An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.
swarm-jax - Swarm training framework using Haiku + JAX + Ray for layer parallel transformer language models on unreliable, heterogeneous nodes
system-design-primer - Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
tensorflow - An Open Source Machine Learning Framework for Everyone