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QwQ: Alibaba's O1-like reasoning LLM

qwenlm.github.io

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Re: QwQ: Alibaba's O1-like reasoning LLM

#41

Post by pkkkzip »

mmastrac wrote: post #4

It seemed to reason through the strawberry problem (though taking a fairly large number of tokens to do so). It fails with history questions though (yes, I realize this is just model censorship): > What happened at Tiananmen Square in 1989? I'm sorry, but I can't assist with that.

Deepseek does this too but honestly I'm not really concerned (not that I dont care about Tianmen Square) as long as I can use it to get stuff done.

Western LLMs also censor and some like Anthropic is extremely sensitive towards anything racial/political much more than ChatGPT and Gemini.

The golden chalice is an uncensored LLM that can run locally but we simply do not have enough VRAM or a way to decentralize the data/inference that will remove the operator from legal liability.

Re: QwQ: Alibaba's O1-like reasoning LLM

#42

Post by syntaxing »

I’m so curious how big Deepseek’s R1-lite is in comparison to this. The Deepseek R1-lite one has been really good so I really hope it’s about the same size and not MoE.

Also I find it interesting how they’re doing a OwO face. Not gonna lie, it’s a fun name.

Re: QwQ: Alibaba's O1-like reasoning LLM

#43

Post by pkkkzip »

syntaxing wrote: post #42

I’m so curious how big Deepseek’s R1-lite is in comparison to this. The Deepseek R1-lite one has been really good so I really hope it’s about the same size and not MoE. Also I find it interesting how they’re doing a OwO face. Not gonna lie, it’s a fun name.

Forgot about R1, what hardware are you using to run it?

Re: QwQ: Alibaba's O1-like reasoning LLM

#44

Post by syntaxing »

pkkkzip wrote: post #43
syntaxing wrote: post #42

I’m so curious how big Deepseek’s R1-lite is in comparison to this. The Deepseek R1-lite one has been really good so I really hope it’s about the same size and not MoE. Also I find it interesting how they’re doing a OwO face. Not gonna lie, it’s a fun name.

Forgot about R1, what hardware are you using to run it?

I haven’t ran QWQ yet, but it’s a 32B. So about 20GB RAM with Q4 quant. Closer to 25GB for the 4_K_M one. You can wait for a day or so for the quantized GGUFs to show up (we should see the Q4 in the next hour or so). I personally use Ollama on an MacBook Pro. It usually takes a day or two for it to show up. Any M series MacBook with 32GB+ of RAM will run this.

Re: QwQ: Alibaba's O1-like reasoning LLM

#45

Post by [deleted] »

syntaxing wrote: post #42

I’m so curious how big Deepseek’s R1-lite is in comparison to this. The Deepseek R1-lite one has been really good so I really hope it’s about the same size and not MoE. Also I find it interesting how they’re doing a OwO face. Not gonna lie, it’s a fun name.

[deleted]

Re: QwQ: Alibaba's O1-like reasoning LLM

#46

Post by titanomachy »

ziml77 wrote: post #40
mmastrac wrote: post #4

It seemed to reason through the strawberry problem (though taking a fairly large number of tokens to do so). It fails with history questions though (yes, I realize this is just model censorship): > What happened at Tiananmen Square in 1989? I'm sorry, but I can't assist with that.

> Who is Xi Jinping? I'm sorry but I can't assist with that. > Who is the leader of China? As an AI language model, I cannot discuss topics related to politics, religion, sex, violence, and the like. If you have other related questions, feel free to ask. So it seems to have a very broad filter on what it will actually respond to.

Well, yeah... it's from China. And you thought Google's PC self-censorship was bad.

Re: QwQ: Alibaba's O1-like reasoning LLM

#47

Post by aledalgrande »

syntaxing wrote: post #44
pkkkzip wrote: post #43

Earlier quoted context omitted.

Forgot about R1, what hardware are you using to run it?

I haven’t ran QWQ yet, but it’s a 32B. So about 20GB RAM with Q4 quant. Closer to 25GB for the 4_K_M one. You can wait for a day or so for the quantized GGUFs to show up (we should see the Q4 in the next hour or so). I personally use Ollama on an MacBook Pro. It usually takes a day or two for it to show up. Any M series MacBook with 32GB+ of RAM will run this.

https://ollama.com/library/qwq

Re: QwQ: Alibaba's O1-like reasoning LLM

#48

Post by jszymborski »

pkkkzip wrote: post #41
mmastrac wrote: post #4

It seemed to reason through the strawberry problem (though taking a fairly large number of tokens to do so). It fails with history questions though (yes, I realize this is just model censorship): > What happened at Tiananmen Square in 1989? I'm sorry, but I can't assist with that.

Deepseek does this too but honestly I'm not really concerned (not that I dont care about Tianmen Square) as long as I can use it to get stuff done. Western LLMs also censor and some like Anthropic is extremely sensitive towards anything racial/political much more than ChatGPT and Gemini. The golden chalice is an uncensored LLM that can run locally but we simply do not have enough VRAM or a way to decentralize the dat…

Ask Anthropic whether the USA has ever comitted war crimes, and it said "yes" and listed ten, including the My Lai Massacre in Vietname and Abu Graib.

The political censorship is not remotely comparable.

Re: QwQ: Alibaba's O1-like reasoning LLM

#49

Post by pitpatagain »

Lucasoato wrote: post #35

> Find the least odd prime factor of 2019^8+1 God that's absurd. The mathematical skills involved on that reasoning are very advanced; the whole process is a bit long but that's impressive for a model that can potentially be self-hosted.

Also probably in the training data: https://www.quora.com/What-is-the-least-odd-prime-factor-of-...

It's a public AIME problem from 2019.

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