BitNet
BitNet is a family of large language model architectures developed by Microsoft Research Asia that constrain the weights of a transformer to extremely low bit-widths: initially a single bit ({-1, +1}) and…
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BitNet is a family of large language model architectures developed by Microsoft Research Asia that constrain the weights of a transformer to extremely low bit-widths: initially a single bit ({-1, +1}) and…
BitNet b1.58 is a ternary-weight large language model architecture from Microsoft Research in which every weight is constrained to one of three values, -1, 0, or +1
The Differential Transformer (often shortened to Diff Transformer or DIFF Transformer) is a decoder-only neural sequence architecture introduced by researchers at Microsoft Research and Tsinghua University in…
LongNet is a transformer variant introduced by Microsoft Research in July 2023 that is designed to scale attention to sequences exceeding one billion tokens while preserving performance on shorter inputs.
LongRoPE is a context-window extension technique for large language models (LLMs) that use rotary position embeddings (RoPE).
YOCO ("You Only Cache Once") is a decoder-decoder neural network architecture for large language models introduced by researchers at Microsoft Research and Tsinghua University in May 2024.