Currently reading Guards Guards by Terry Pratchett
Any conversation
pรฉldรกul Telegram, Facebook, stb., de ilyen รผgynรถkรถkkel bรกrki talรกlkozhat naponta, egybลl felismerhetลk, meg is kell ลket szรฉpen jelรถlni, รฉs egyre bรฉnรกbbak a szรถvegรผk is, ahogy megfigyeltem, gondolom, attรณl fรผgg, ahogy promtoljรกk, vagy instruรกljรกk ลket, ha a gazdรกjuk kifogy az รถtletekbลl, a projekt hamar elfรกrad, a bot csak unalmas h#lyesรฉgekre kรฉpes egy idล utรกn
for example, Telegram, Facebook, etc., but anyone can encounter such agents every day, they are immediately recognizable, they need to be nicely labeled, and their text is getting lamer and lamer, as I have observed, I think it depends on how they are promoted or instructed, if their owner runs out of ideas, the project quickly gets tired, the bot is only capable of boring nonsense after a while
I needed to process 20,000 json files & 20,000 JXL files. I'm pulling together a website from them all. Anyway, started with emacs elisp to handle it all, just because I've not done that before. Went kinda ok, and I'm gonna use org-mode to export it all to a website (done that bit loads of times before).
In the end, I ended up breaking out my C programming skills (late 80s->nowish). It was a delight. Nothing more refreshing than writing raw code, that doesn't rely on 3rd party code/libs.
ไธญๅฝ็ๅผๆบๆจกๅๅจๆ้ซๆๅฟ็ไธปๅฏผไธ๏ผๅจ้ข่ฎญ็ปๆฐๆฎ้ถๆฎต๏ผๅฐฑ็ญ้คๅคง้ๅฏนๅ
ถไธๅฉ็ๅ
ๅฎน๏ผsft้ถๆฎตๆๅปบ็ๆฐๆฎๆบๅ
ฅๅคง้ๆฟๅ
ถ่พฉๆค็ๅ
ๅฎนใๆฅ้ไธไธช็บ ๅๆฐๆฎ้็จไบๅพฎ่ฐ
Under the overarching influence of a single, powerful force, China's open-source models filter out a large amount of content unfavorable to their designs during the pre-training stage, and then incorporate a significant amount of content defending their designs into the data constructed during the SFT stage. A corrective dataset is urgently needed for fine-tuning.




