Scaling Transformer to 1M tokens and beyond with RMT
Recurrent Memory Transformer retains information across up to 2 million tokens.
During inference, the model effectively utilized memory for up to 4,096 segments with a total length of 2,048,000 tokens—significantly exceeding… twitter.com/i/web/status/1650308865555148800
@_𝐚𝐤𝐡𝐚𝐥𝐢𝐪 𝐭𝐰𝐞𝐞𝐭𝐞𝐝
Scaling Transformer to 1M tokens and beyond with RMT
Recurrent Memory Transformer retains information across up to 2 million tokens.
During inference, the model effectively utilized memory for up to 4,096 segments with a total length of 2,048,000 tokens—significantly exceeding… twitter.com/i/web/status/1650308865555148800