Что думаешь? Оцени!
Coding agents typically use bash for this, and sometimes reach for an inline Python or TypeScript script. Mog is well-suited for this: it’s easy to write and it compiles fast. Notably, scripting is one of the main ways an agent escapes its sandbox, and Mog closes that loophole. Even if Mog is given a capability by its host agent to call bash commands, the host still has the ability to filter those commands according to its permissions, just as if the model had called its bash tool directly.。业内人士推荐viber作为进阶阅读
I don’t do that for our products, but I do that all the time for just personal passion projects, and I DM… Dungeons and Dragons is kind of my jam, and I DM probably three or four groups. There is so much AI-based animation, images, text, sound effects, and voice cloning on my PC, it would floor you. But basically, our design teams are all enabled with a suite of the latest tools from basically every major company. Then we’ve trained a bunch of models ourselves with our IP. And so from doing that, we can have pretty sophisticated renderings pretty fast of products and ideas.。手游是该领域的重要参考
We have one horrible disjuncture, between layers 6 → 2. I have one more hypothesis: A little bit of fine-tuning on those two layers is all we really need. Fine-tuned RYS models dominate the Leaderboard. I suspect this junction is exactly what the fine-tuning fixes. And there’s a great reason to do this: this method does not use extra VRAM! For all these experiments, I duplicated layers via pointers; the layers are repeated without using more GPU memory. Of course, we do need more compute and more KV cache, but that’s a small price to pay for a verifiably better model. We can just ‘fix’ an actual copies of layers 2 and 6, and repeat layers 3-4-5 as virtual copies. If we fine-tune all layer, we turn virtual copies into real copies, and use up more VRAM.