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20:28
YouTube
Outlier
Rotary Positional Embeddings Explained | Transformer
In this video I'm going through RoPE (Rotary Positional Embeddings) which is a key method in Transformer models of any modality - text, image or video. RoPE is used to teach Transformers about positions in your input data. For example which text tokens come first in a sentence or how frames are ordered in a video. It is a necessity if you are ...
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RoFormer: Enhanced Transformer with Rotary Position Embedding RoFormer Paper Review
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【双语】Why Rotating Vectors Solves Positional Encoding in Transformers | ROPE
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