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DeepSeek-v3.1

api-docs.deepseek.com

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Re: DeepSeek-v3.1

#191

Post by solarkraft »

mkl wrote: post #132
danielhanchen wrote: post #85

Earlier quoted context omitted.

Thanks for the suggestions! Apologies again I'm pretty bad at packaging, so hence the current setup. 1. So I added a `check_llama_cpp` which checks if llama.cpp does exist and it'll use the prebuilt one https://github.com/unslothai/unsloth-zoo/blob/main/unsloth_z... 2. Yes I like the idea of determining distro 3. Agreed on bailing - I was also thinking if doing a Python input() with a 30 second waiting period for apt…

It shouldn't install any packages itself. Just print out a message about the missing packages and your guess of the command to install them, then exit. That way users can run the command themselves if it's appropriate or add the packages to their container build or whatever. People set up machines in a lot of different ways, and automatically installing things is going to mess that up.

This is an edge case optimization at the cost of 95% of users.

Re: DeepSeek-v3.1

#192

Post by solarkraft »

danielhanchen wrote: post #146
mkl wrote: post #142

Earlier quoted context omitted.

Yes, since you won't actually need the permissions.

Hmmm I'm worried people will really not get on how to install / compile / use the terminal hmmm hence I thought permissions were like a compromise solution

I think that it is, quite a good one, even:

- Determine the command that has to be run by the algorithm above.

This does most of the work a user would have to figure out what has to be installed on their system.

- Ask whether to run the command automatically.

This allows the “software should never install dependencies by itself” crowd to say no and figure out further steps, while allowing people who just want it to work to get on with their task as quickly as possible (who do you think there are more of?).

I think it would be fine to print out the command and force the user to run it themselves, but it would bring little material gain at the cost of some of your users’ peace (“oh no it failed, what is it this time ...”).

Re: DeepSeek-v3.1

#193

Post by edg5000 »

unleaded wrote: post #130

not sure if its just chat.deepseek.com but one strange thing I've noticed is that now it replies to like 90% of your questions with "Of course.", even when it doesnt fit the prompt at all. maybe it's the backend injecting it to be more obedient? but you can tell it `don't begin the reply to this with "of" ending "course"` and it will listen. it's very strange Some people on reddit (very reliable source I know) are sa…

> for example it does that annoying thing gemini does now where when you use slang or really any informal terms it puts them in quotes in its reply

Haven´t used Gemini much, but the time I used it, it felt very academic and theoretical compared to Opus 4. So that seems to fit. But I'll have to do more evaluation of the non-Claude models to get a better idea of the differences.

Re: DeepSeek-v3.1

#194

Post by merelysounds »

irthomasthomas wrote: post #157
dmos62 wrote: post #145

Earlier quoted context omitted.

How do you propose that would work? A pipeline that goes through query-response pairs to deduce response quality and then uses the low-quality responses for further training? Wouldn't you need a model that's already smart enough to tell that previous model's responses weren't smart enough? Sounds like a chicken and egg problem.

It just means that once you send your test questions to a model API, that company now has your test. So 'private' benchmarks take it on faith that the companies won't look at those requests and tune their models or prompts to beat them.

Would the model owners be able to identify the benchmarking session among many other similar requests?

Re: DeepSeek-v3.1

#195

Post by rpdillon »

danielhanchen wrote: post #178
rat9988 wrote: post #152

Earlier quoted context omitted.

Don't worry. Don't let the rednecks screaming here affect you. As for one, I'm happy that you have automated this part and sad to see it is going away. People will always complain. It might be reasonable feedback worth acting upon. Don't let their tone distract you though. Some of them are just angry all day.

Thanks - hopefully the compromise solution ie python input asking for user permissions works ok?

As a guy that would naturally be in the camp of "installing packages is never okay", I also live in the more practical world where people want things to work. I think the compromise you're suggesting is a pretty good one. I think the highest quality implementation here would be.

Try to find prebuilt and download.

See if you can compile from source if a compiler is installed.

If no compiler: prompt to install via sudo apt and explaining why, also give option to abort and have the user install a compiler themselves.

This isn't perfect, but limits the cases where prompting is necessary.

Re: DeepSeek-v3.1

#196

Post by irthomasthomas »

merelysounds wrote: post #194
irthomasthomas wrote: post #157

Earlier quoted context omitted.

It just means that once you send your test questions to a model API, that company now has your test. So 'private' benchmarks take it on faith that the companies won't look at those requests and tune their models or prompts to beat them.

Would the model owners be able to identify the benchmarking session among many other similar requests?

Depends. Something like arc-agi might be easy as it follows a defined format. I would also guess that the usage pattern for someone running a benchmark will be quite distinct from that of a normal user, unless they take specific measures to try to blend in.

Re: DeepSeek-v3.1

#197

Post by linuxftw »

segmondy wrote: post #181
tw1984 wrote: post #72

Earlier quoted context omitted.

for such dynamic 2bit, is there any benchmark results showing how many performance I would give up compared to the original model? thanks.

if you are running a 2bit quant, you are not giving up performance but gaining 100% performance since the alternative is usually 0%. Smaller quants are for folks who won't be able to run anything at all, so you run the largest you can run relative to your hardware. I for instance often ran Q3_K_L, I don't think of how much performance I'm giving up, but rather how without Q3, I won't be able to run it at all. With th…

That's true only in a vacuum. For example, should I run gpt-oss-20b unquantized or gpt-oss-120b quantaized? Some models have a 70b/30b spread, and that's only across a single base model, where many different models exist at different quants could be compared for different tasks.

Re: DeepSeek-v3.1

#198

Post by pradn »

edg5000 wrote: post #193
unleaded wrote: post #130

not sure if its just chat.deepseek.com but one strange thing I've noticed is that now it replies to like 90% of your questions with "Of course.", even when it doesnt fit the prompt at all. maybe it's the backend injecting it to be more obedient? but you can tell it `don't begin the reply to this with "of" ending "course"` and it will listen. it's very strange Some people on reddit (very reliable source I know) are sa…

> for example it does that annoying thing gemini does now where when you use slang or really any informal terms it puts them in quotes in its reply Haven´t used Gemini much, but the time I used it, it felt very academic and theoretical compared to Opus 4. So that seems to fit. But I'll have to do more evaluation of the non-Claude models to get a better idea of the differences.

All this points to "personality" being a big -- and sticky -- selling point for consumer-facing chat bots. People really did like the chatty, emoji-filled persona of the previous ChatGPT models. So OpenAI was ~forced to adjust GPT-5 to be closer to that style.

It raises a funny "innovator's dilemma" that might happen. Where an incumbent has to serve chatty consumers, and therefore gets little technical/professional training data. And a more sober workplace chatbot provider is able to advance past the incumbent because they have better training data. Or maybe in a more subtle way, chatbot personas give you access to varying market segments, and varying data flywheels.

Re: DeepSeek-v3.1

#199

Post by bgilroy26 »

Leynos wrote: post #134
xmichael909 wrote: post #40

Seems to hallucinate more than any model I've ever worked with in the past 6 months.

DeepSeek is bad for hallucinations in my experience. I wouldn't trust its output for anything serious without heavy grounding. It's great for fantastical fiction though. It also excels at giving characters "agency".

Where would you go to find people posting their AI generated fiction? I haven't been able to find it on Reddit

Re: DeepSeek-v3.1

#200

Post by mkl »

solarkraft wrote: post #191
mkl wrote: post #132

Earlier quoted context omitted.

It shouldn't install any packages itself. Just print out a message about the missing packages and your guess of the command to install them, then exit. That way users can run the command themselves if it's appropriate or add the packages to their container build or whatever. People set up machines in a lot of different ways, and automatically installing things is going to mess that up.

This is an edge case optimization at the cost of 95% of users.

95% of users probably won't be using Linux. Most of those who are will have no problem installing dependencies. There are too many distributions and ways of setting them up for automated package manager use to be the right thing to do. I have never seen a Python package even try.
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