Giter Club home page Giter Club logo

Comments (3)

moyix avatar moyix commented on March 29, 2024

It depends a lot on the output of the model unfortunately! The Copilot plugin typically makes requests for 500 tokens, which can take a long time for FauxPilot (~24.8 seconds in a quick test I did just now with a single A6000 and the 16B model). But most of these requests tell the model to stop generating when it emits a newline, so it doesn't end up generating anywhere near 500 tokens and the model finishes much faster. With the 16B model on an A6000 can expect it to take ~50ms per token generated.

Occasionally, like when you are at the start of a function, Copilot will make a request that tries to generate a longer chunk of code (by stopping on sequences like \ndef or \nif), and that can be a bit slower (it's slower in the official Copilot as well).

If you have multiple GPUs you can generally expect the latency to decrease almost linearly (so two A6000s can generate almost twice as fast).

If you were trying to use this to serve many clients at once, you might be able to batch together multiple requests that come in at the same time, which would give you better throughput overall; I believe the underlying Triton inference server does support this.

In any case, improving inference latency is definitely something I'm interested in! But I think that will probably require looking at techniques like model compression and quantization.

from fauxpilot.

moyix avatar moyix commented on March 29, 2024

Also, if you happen to put together something that tries to benchmark this with some real-world code using the kinds of requests Copilot makes I'd definitely be curious to see the results!

from fauxpilot.

nashid avatar nashid commented on March 29, 2024

@moyix curious to know what happens to the concurrent requests to fauxpilot. Those concurrent requests would be queued and would be served eventually? Is there a limit of how many concurrent requests could be made? Or the concurrent requests would be lost?

from fauxpilot.

Related Issues (20)

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.