Скачать с ютуб Google MUSE Text To Image Generation AI Architecture First Look в хорошем качестве

Google MUSE Text To Image Generation AI Architecture First Look

In this video I explain about Google Muse Text To Image Generation AI. Muse, a text-to-image Transformer model that achieves state-of-the-art image generation performance while being significantly more efficient than diffusion or autoregressive models. Muse is trained on a masked modeling task in discrete token space: given the text embedding extracted from a pre-trained large language model (LLM), Muse is trained to predict randomly masked image tokens. Compared to pixel-space diffusion models, such as Imagen and DALL-E 2, Muse is significantly more efficient due to the use of discrete tokens and requiring fewer sampling iterations; compared to autoregressive models, such as Parti, Muse is more efficient due to the use of parallel decoding. The use of a pre-trained LLM enables fine-grained language understanding, translating to high-fidelity image generation and the understanding of visual concepts such as objects, their spatial relationships, pose, cardinality, etc. If you like such content please subscribe to the channel here: https://www.youtube.com/c/RitheshSree... If you like to support me financially, It is totally optional and voluntary. Buy me a coffee here: https://www.buymeacoffee.com/rithesh Relevant Links: https://muse-model.github.io/ https://compvis.github.io/taming-tran... https://ljvmiranda921.github.io/noteb...