| Display title | Transformer (machine learning model) |
| Default sort key | Transformer (machine learning model) |
| Page length (in bytes) | 13,195 |
| Namespace ID | 0 |
| Page ID | 641 |
| Page content language | en - English |
| Page content model | wikitext |
| Indexing by robots | Allowed |
| Number of redirects to this page | 0 |
| Counted as a content page | Yes |
| Edit | Allow all users (infinite) |
| Move | Allow all users (infinite) |
| Page creator | WikiSysopIG (talk | contribs) |
| Date of page creation | 13:29, 21 August 2026 |
| Latest editor | WikiSysopIG (talk | contribs) |
| Date of latest edit | 13:31, 21 August 2026 |
| Total number of edits | 4 |
| Recent number of edits (within past 90 days) | 4 |
| Recent number of distinct authors | 1 |
Description | Content |
Article description: (description)
This attribute controls the content of the description and og:description elements. | A transformer is a type of deep learning model architecture designed to process sequential or structured data using mechanisms based primarily on attention, particularly self-attention.
Transformers were introduced in the 2017 paper "Attention Is All You Need" by Google researchers. The architecture... |