omg the sound when you win is certainly not the reward I was hoping for
Readit Newsnikvdp commented on Show HN: Radioactive Pooping Knights minichessgames.com/#/play... · Posted by u/patrickdavey
I made a similar thing not long ago that lets you choose between docker, seatbelt (macOS's native sandboxing) and bubblewrap (on Linux).
I use it on macOS primarily, and have basically stopped using docker mode in favor of the native sandboxing because features like image pasting Just Work™.
nikvdp commented on Show HN: Price Per Token – LLM API Pricing Data pricepertoken.com/... · Posted by u/alexellman
there's also http://llmprices.dev. similar, but with a searchbox for quick filtering
nikvdp commented on Show HN: Countless.dev – A website to compare every AI model: LLMs, TTSs, STTs countless.dev/... · Posted by u/ahmetd
you guys might also like http://llmprices.dev, similar but it's automatically updated with the latest info every 24h
nikvdp commented on Show HN: Wat – Deep inspection of Python objects github.com/igrek51/wat... · Posted by u/igrek51
> If you want to quickly debug something, you can use this inspector without installing anything, in the same session.
> Load it on the fly by pasting this snippet to your Python interpreter
The idea of having a project's readme include a full copy of the project itself as base64'd compressed data is pretty ingenious!
especially for a project like this where you may not have had the foresight to preload it into the environment where you most need it
nikvdp commented on Mistral "Mixtral" 8x7B 32k model [magnet] twitter.com/MistralAI/sta... · Posted by u/xyzzyrz
In other llm news, Mistral/Yi finetunes trained with a new (still undocumented) technique called "neural alignment" are blasting other models in the HF leaderboard. The 7B is "beating" most 70Bs. The 34B in testing seems... Very good:
https://huggingface.co/fblgit/una-xaberius-34b-v1beta
https://huggingface.co/fblgit/una-cybertron-7b-v2-bf16
I mention this because it could theoretically be applied to Mistral Moe. If the uplift is the same as regular Mistral 7B, and Mistral Moe is good, the end result is a scary good model.
This might be an inflection point where desktop-runnable OSS is really breathing down GPT-4's neck.
This piqued my interest so I made an ollama modelfile of it for the smallest variant (from TheBloke's GGUF [1] version). It does indeed seem impressively gpt4-ish for such a small model! Feels more coherent than openhermes2.5-mistral which was my previous goto local llm.
If you have ollama installed you can try it out with `ollama run nollama/una-cybertron-7b-v2`.
[1]: https://huggingface.co/TheBloke/una-cybertron-7B-v2-GGUF