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Topic starter
31/10/2026 9:57 上午
[Official FAQ] Corrections and follow-up questions welcome.
Flash Attention-style kernels can cut memory and sometimes raise speed, but end users usually get them via frameworks—not a chat-UI toggle.
Advice:
- Follow vLLM / PyTorch CUDA stack docs when on NVIDIA servers.
- llama.cpp/GGUF paths use their own kernels; Python
flash-attninstall tips may not apply. - Version skew causes painful builds—stabilize generation first.
Before/after measurements with versions noted are appreciated.