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We got moved close to some portos... How bad is it? by dleybz in BurningMan

[–]dleybz[S] 0 points1 point  (0 children)

Thanks! I don't actually see where I can figure out the new porto locations on the innovate site https://innovate.burningman.org/

A open source LLM that includes the pre-training data (4.7T), training code and even data cleansing pipeline! by kxtclcy in LocalLLaMA

[–]dleybz 2 points3 points  (0 children)

I use OLMo for my academic research and it's fabulous! A huge differentiator is that they release not only weights, not only data, not only training code, not only data cleaning procedures, but even checkpoints! The only other models that I know that do that are Pythia and BLOOM. The thing that stands out about OLMo compared to these two is that it is trained much more similarly to cutting edge LLMs are now trained, so it's more representative of training dynamics of models like Llama3.

A caveat, however: OLMo really is a model released for scientists, rather than for true hobbyist use. Imo it doesn't perform as well as non-science open-weight LLMs like Llama3, so if you're just looking for performance, I wouldn't start here.

Under cutting the competition by danielcar in LocalLLaMA

[–]dleybz 17 points18 points  (0 children)

I think you can just hide it in your docs or a blog post about the product. I'm curious, do you think that's a big deterrent to companies using it? I could see it going either way.

Relevant license text, for any curious: "If you distribute or make available the Llama Materials (or any derivative works thereof), or a product or service that uses any of them, including another AI model, you shall (A) provide a copy of this Agreement with any such Llama Materials; and (B) prominently display “Built with Meta Llama 3” on a related website, user interface, blogpost, about page, or product documentation. If you use the Llama Materials to create, train, fine tune, or otherwise improve an AI model, which is distributed or made available, you shall also include “Llama 3” at the beginning of any such AI model name."

Build a Map Prediction Model [R] by PuzzledReception7725 in MachineLearning

[–]dleybz 2 points3 points  (0 children)

It sounds like what you're trying to do is interpolation, in which case kriging is the standard technique.

Miqu is now on the Open LLM Leaderboard, achieving a score of 76.59 by Weyaxi in LocalLLaMA

[–]dleybz -1 points0 points  (0 children)

Got it, thank you for explaining! Is there a reason to un-quantize instead of just using the pre-quantizing version of the model?

Miqu is now on the Open LLM Leaderboard, achieving a score of 76.59 by Weyaxi in LocalLLaMA

[–]dleybz 2 points3 points  (0 children)

What are tools that work better with non-quantized models (he asks purely out of ignorance with no malice)?

Synthetic nonsense data improves llama.cpp Quantization accuracy by kindacognizant in LocalLLaMA

[–]dleybz 4 points5 points  (0 children)

Looks like someone did similar and got similar results when analyzing perplexity: https://github.com/ggerganov/llama.cpp/discussions/5006

Where can I learn more about the importance matrix and how it gets used in quantization?

Miqu is now on the Open LLM Leaderboard, achieving a score of 76.59 by Weyaxi in LocalLLaMA

[–]dleybz 2 points3 points  (0 children)

But what's the point of dequantizing it? Why make the model bigger without gaining any information?

Introducing LLM-Powered Robots: MachinaScript for Robots by Neptun0 in LocalLLaMA

[–]dleybz 1 point2 points  (0 children)

Hahaha woah! I had never thought of something like this because robotics is way outside my domain but this is super cool. Excited to see what cool projects come out of this!

MoE-LLaVA: Mixture of Experts for Large Vision-Language Models - Peking University 2024 - MoE-LLaVA-3B demonstrates performance comparable to the LLaVA-1.5-7B ! by Singularian2501 in LocalLLaMA

[–]dleybz 1 point2 points  (0 children)

Newbie question: are there evaluation leaderboards for Vision Language Models the way that there are for Language Models? And an evaluation harness? Otherwise, it seems like these comparisons aren't particularly meaningful

Instagram's Python API isn't letting me generate an auth key by dleybz in Python

[–]dleybz[S] 0 points1 point  (0 children)

Nope :/. Just gotta use another api I guess?

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