Transformer Decoder Architecture | Deep Learning | CampusX
The Decoder in a transformer architecture generates output sequences by attending to both the previous tokens (via masked self-attention) and the encoder’s output (via cross-attention). Each decoder layer consists of multi-head self-attention, cross-attention, and feed-forward layers. This structure allows the model to generate coherent sequences by considering both past outputs and relevant input context, making it effective for tasks like text generation and translation.
Digital Notes for Deep Learning: https://shorturl.at/NGtXg
============================
Did you like my teaching style?
Check my affordable mentorship program at : https://learnwith.campusx.in
DSMP FAQ: https://docs.google.com/document/d/1O...
============================
📱 Grow with us:
CampusX' LinkedIn: / campusx-official
Slide into our DMs: / campusx.official
My LinkedIn: / nitish-singh-03412789
Discord: / discord
E-mail us at support@campusx.in
⌚Time Stamps⌚
00:00 - Plan of Attack
02:22 - Simplified View
10:10 - Deep Dive into Architecture
En esta página del sitio puede ver el video en línea Transformer Decoder Architecture | Deep Learning | CampusX de Duración hora minuto segunda en buena calidad , que subió el usuario CampusX 22 agosto 2024, comparta el enlace con amigos y conocidos, en youtube este video ya ha sido visto 7,591 veces y le gustó 451 a los espectadores. Disfruta viendo!
