humanspiral@lemmy.ca to

LocalLLaMA@sh.itjust.worksEnglish · 7 months ago

autoround (optimized for intel but works on amd) integer quantization provides good CPU performance, and good accuracy benchmarks.

1

0

autoround (optimized for intel but works on amd) integer quantization provides good CPU performance, and good accuracy benchmarks.

humanspiral@lemmy.ca to

LocalLLaMA@sh.itjust.worksEnglish · 7 months ago

1

GitHub - intel/auto-round: A SOTA quantization algorithm for high-accuracy low-bit LLM inference, seamlessly optimized for CPU/XPU/CUDA, with multi-datatype support and full compatibility with vLLM, SGLang, and Transformers.

A SOTA quantization algorithm for high-accuracy low-bit LLM inference, seamlessly optimized for CPU/XPU/CUDA, with multi-datatype support and full compatibility with vLLM, SGLang, and Transformers....

You must log in or # to comment.

Chat

hendrik@palaver.p3x.de
link
fedilink
English
arrow-up
1·
edit-2
7 months ago
So… Any context on how it compares to other quantization techniques? Is it faster or slower at similar accuracy?

LocalLLaMA@sh.itjust.works

localllama@sh.itjust.works

You are not logged in. However you can subscribe from another Fediverse account, for example Lemmy or Mastodon. To do this, paste the following into the search field of your instance: [email protected]

Welcome to LocalLLaMA! Here we discuss running and developing machine learning models at home. Lets explore cutting edge open source neural network technology together.

Get support from the community! Ask questions, share prompts, discuss benchmarks, get hyped at the latest and greatest model releases! Enjoy talking about our awesome hobby.

As ambassadors of the self-hosting machine learning community, we strive to support each other and share our enthusiasm in a positive constructive way.

Rules:

Rule 1 - No harassment or personal character attacks of community members. I.E no namecalling, no generalizing entire groups of people that make up our community, no baseless personal insults.

Rule 2 - No comparing artificial intelligence/machine learning models to cryptocurrency. I.E no comparing the usefulness of models to that of NFTs, no comparing the resource usage required to train a model is anything close to maintaining a blockchain/ mining for crypto, no implying its just a fad/bubble that will leave people with nothing of value when it burst.

Rule 3 - No comparing artificial intelligence/machine learning to simple text prediction algorithms. I.E statements such as "llms are basically just simple text predictions like what your phone keyboard autocorrect uses, and they’re still using the same algorithms since <over 10 years ago>.

Rule 4 - No implying that models are devoid of purpose or potential for enriching peoples lives.

Visibility: Public

This community can be federated to other instances and be posted/commented in by their users.

21 users / day
55 users / week
76 users / month
82 users / 6 months
1 local subscriber
4.69K subscribers
52 Posts
112 Comments
Modlog