Tools · MarkTechPost ·
How to Build Memory-Efficient Transformers with xFormers Using Packed Sequences, GQA, ALiBi, SwiGLU, and Causal Attention
The post shows how to use xFormers to build a GPU-efficient Transformer and verifies memory-efficient attention against a standard implementation. It also covers packed variable-length sequences, causal masking, grouped-query attention, ALiBi, SwiGLU, and mixed-precision training in a GPT-style model.