drplan

DMed you

https://preview.redd.it/73h3ap3922eg1.jpeg?width=4284&format=pjpg&auto=webp&s=25b762fd6e09bee7db6d4570176a6a4459b3116a Yes 🙂

As for the decompilers: DeDe and IDR seem to be a start?

I would strongly doubt AI can deal with disassembled ASM on full application scale. Info loss is to be expected with decompilation, however the overall logic should be recognisable. And what AI is fairly OK at, is explaining existing code bases. So create a readable codebase with decompiler, open the directory in cursor, ans ask questions. As far as i remember many decompilers have the option to reference disassembly in the decompiled code.

I think my approach would be to use a decompiler first and align the dissassembly with it. Identify the relevant pieces, then analyze where/what you need to change with AI help.

Wow 😮 Could one get this work on a an AMD 395?

Seems like a MINOR problem...

The weird noises of me grumbling of envy

No it was included. We post more when i have it up and running. Documentation is lacking.

https://preview.redd.it/teur16fnbi0g1.jpeg?width=3840&format=pjpg&auto=webp&s=a5a0653b72d2c4984cf16627f8906f4c96be076e Here it is

Direkt von Sixunited. Wenn Du eins brauchst, lass es mich wissen. Ich importiere demnächst wahrscheinlich eine Charge.

Brutal rig. How do you make so much money with a fruit shop?

Thanks !!!

Thanks mate, this is awesome. Can you share a script on how you exactly compiled the Strix Halo optimal version of llama.cpp? That would be super-useful.

PCIE x16 Expansion slot. Otherwise same.

Wondering, how they are doing it. I am currently importing a Sixunited STHT1 board. 1581 € /which would include 19% taxes in Germany so it is 1328 € net) leaves no margin. They must have gotten an impressive deal with Six United.

This is the stuff, this channel was made for. Congrats!

I can't express how much I love this.

Finally LocalMechaHitler SCNR

Well the benchmarks do not seem very good at least, from what I am reading. My first test are OKish, however capabilities on languages other than English seem limited. Do not get me wrong, there is lots of potential. Benchmarks will tell us where these models will find their place.

Jep, can we all agree on that the models are not very good, but that the architecture choices have the potential to move the needle performance-wise?

Prompt literally contains the words "red-pilled truth", which implies well... truth?

OPs prompt implied alignment with the ideology. The models responds if you ask in a neutral way. https://preview.redd.it/4zqh2x570dhf1.png?width=1936&format=png&auto=webp&s=b83ef734816b82ab6ea70fb4a6ae192acd199a7c

Actually, in this specific case, I am relieved.

Performance on AMD AI Max 395 using llama.cpp on gpt-oss-20b is pretty decent. ./llama-bench -m /home/denkbox/models/gpt-oss-20b-F16.gguf --n-gpu-layers 100 warning: asserts enabled, performance may be affected warning: debug build, performance may be affected ggml\_vulkan: Found 1 Vulkan devices: ggml\_vulkan: 0 = Radeon 8060S Graphics (RADV GFX1151) (radv) | uma: 1 | fp16: 1 | bf16: 0 | warp size: 64 | shared memory: 65536 | int dot: 1 | matrix cores: KHR\_coopmat register\_backend: registered backend Vulkan (1 devices) register\_device: registered device Vulkan0 (Radeon 8060S Graphics (RADV GFX1151)) register\_backend: registered backend CPU (1 devices) register\_device: registered device CPU (AMD RYZEN AI MAX+ 395 w/ Radeon 8060S) load\_backend: failed to find ggml\_backend\_init in /home/denkbox/software/llama.cpp/build/bin/libggml-vulkan.so load\_backend: failed to find ggml\_backend\_init in /home/denkbox/software/llama.cpp/build/bin/libggml-cpu.so | model                          |       size |     params | backend    | ngl |            test |                  t/s | | ------------------------------ | ---------: | ---------: | ---------- | --: | --------------: | -------------------: | | gpt-oss ?B F16                 |  12.83 GiB |    20.91 B | Vulkan     | 100 |           pp512 |        485.92 ± 4.69 | | gpt-oss ?B F16                 |  12.83 GiB |    20.91 B | Vulkan     | 100 |           tg128 |         44.02 ± 0.31 |

I've been running the system on Fedora, no major problems there. Can you post some code to reproduce?

I do not understand. Why the cables?

Aside from the benchmarks, I see quantification in the light of biological neural processing also relying on approximate "calculations". Using full precision is simply bad use of resources.

Do you have any sources for this? Thanks!

Nice! Can you share more pics of the case?

Um. This might be a stupid idea.. but couldn't one try to "enhance" older adventure games (e.g. Monkey Island, Indiana Jones, etc.) by parsing the available SCUMM files? I know, i know sacrilege... but this could be a fun experiment?

Ok, you are right: the compounds are halogenated hydrocarbons, not CFCs. Sorry not a chemist ;)

+Prompt should smell and taste like Red Bull

Uhm the solutions look like Chlorofluorocarbons? Isn't that old stuff and bad for the ozone layer?

Yes real but honestly not worth it…

All of them. However for LLM only Mac OS and Linux.

Fascist owner, not interested

You want to pseudonymize relevant identifiers (like names, credit numbers, etc.)? There are projects/services out there doing this. [https://www.nymiz.com/ai-and-data-anonymization/](https://www.nymiz.com/ai-and-data-anonymization/)

RemindMe! 1 Day

If a model is cheaper and better, it "dominates" the models which are more expensive and worse. However if a model is only cheaper but not better, or better but more expensive, it cannot be really compared, because it is up to individual priorities to rank both properties. If it is wins in both aspects, there is no discussion (given that these aspects are the only variables looked at for deciding).

A model is on the pareto front if no other model is both cheaper and better at the same time. https://preview.redd.it/jarpfkzui7ve1.png?width=3126&format=png&auto=webp&s=3ee644770935ae27331e56acdddba95a2e7ed270

Gemma/Gemini owning the pareto front...

Well, the go-to nowadays to publish code would be github. \- Go to [https://github.com](https://github.com) , Click + → New repository, name it, Click Create repository \- On the new repo page, click the button "Add file" → "Upload files", Drag & drop the .py file, click "Commit changes"

Thanks for this - super useful in any pro-local discussions/slides

You realize you are on r/LocalLLaMA right ;) ? Also I do not agree with the ideology thing, it's also an IP / confidentiality issues that matters in some professional environments. [continue.dev](http://continue.dev) is OK, but not as great. It's not just the models with Cursor, it's also the preprocessing / prompting. .

Exactly... this sucks. I will also try Aider, but it looks too "vibe cody" to me.

Well they "only" raised 125k in 2021. After this nothing seems to have happened, at least not according to Crunchbase.

I like the machine, a step in the right direction, however the price is out of range for the 99% of all hobbyists. We have to accept that it will remain so for some years to come. And when it has come down in price eventually the required specs for SOTA models will have gone up. Running SOTA models locally will always be expensive and/or require creative efforts. Which is part of its charm.

I really like that your project is a compact python script :) Finally an implementation that is easy to follow. Wonderful achievement!

Open-webui looks great, but yes it seems to lack requirement 2. Not sure where to start the modifications.