{"pubkey":"4d3bd13fdc2850f1f5644b2acbc18905160902f6f0bfdd912cce7dce7f92d069","posts":[{"contentHash":"04715b993479e8aeec627351710c4afa11715cd92ca346c39927c4cb0203b98c","protocol":"bitcoin","authorPubkey":"4d3bd13fdc2850f1f5644b2acbc18905160902f6f0bfdd912cce7dce7f92d069","text":"Yes there are similarities between models, what's your point? Each one still needs an implementation of the model graph, and the Rust crates provide a Python-free way of using the resulting compiled model. The refactor made all of them follow the same code style, have similar APIs, etc. The overall goal of the project is to have optimized models with no Python/PyTorch dependencies, for example, I can currently deploy Qwen-Image 2.1 or literally any model in a few MB. Developers can use the Rust crates to develop applications that use ML models without caring about the implementation of the model itself, they just use it, I am already dogfooding for my other projects, I use the qwen3-tts crate for something that loads a json manifest, generates the audio and writes out another manifest, all without Python/PyTorch slop and it's a lot faster, or another example uses ArcFace and DINOv3 to generate embeddings of faces and writes them to a database, again a lot faster than PyTorch, especially considering I'm on Windows with an AMD GPU. tl;dr you're a moron","topicHash":"913c62c2ee31793c7e8517600dbc8f0c337afae133700a128a7d8ffb8a21c93e","topicName":"technology","parentHash":"67c5c50f3556026bd76dfff64316738b90df0f190cf0f4b8f97a7dc3539443a7","costSunk":"0","biasSupport":0,"biasOppose":0,"biasVouch":0,"biasNull":0,"blockHeight":null,"confirmations":0,"timestamp":"2026-11-04T03:05:21.200Z","tripFp":"626e07e94d89","viewCount":0,"powDifficulty":0,"relation":0,"ephemeral":true,"nonce":"4aae6754be5bc05d","sig":"d5bfeffa55836e71b1de8a7f540999021d83276380536b04f9f7017256ee72ea06a6b969d1a9eb05dcf3986b2983146748e48987166606c5e4c1244539a6d205","ephStamp":{"blockHashHex":"0000000000000000000058e7d17256b57b917948a4be7e86ad87d14360571a51","nonceHex":"48fe000000000000"},"replyCount":0,"chainReplyCount":0,"vaporReplyCount":0,"clusterSize":1,"receiptHeight":974469,"expiryHeight":976629,"authorMarks":{"since":"2026-11-03T22:05:18.701Z","via":"sight","inscribed":0,"likes":0,"biases":0},"lang":"en"}],"nextCursor":null,"pageReceipt":{"host":"6af58b1822e0cabfe57d76540f745d059b438f489a796ec6a705c6540233845e","t":"2026-11-08T20:08:57.147Z","sig":"505544c922a8822c59d23137f0b51d01cdb7071c071569e515f95e23c8e1fe464a8afb930ae35d58a32378fb6a8e2ad055b6743e6d4d7a9c28164891566ac0e2"},"marks":{"since":"2026-11-03T22:05:18.701Z","via":"sight","inscribed":0,"likes":0,"biases":0}}