Rwkv Architecture
원문: rwkv-architecture
RNN+Transformer hybrid with O(n) inference. Linear time, infinite context, no KV cache. Train like GPT (parallel), infer like RNN (sequential). Linux Foundation AI project. Production at Windows, Office, NeMo. RWKV-7 (March 2025). Models up to 14B parameters.
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RWKV Receptance Weighted Key Value Quick start RWKV (RwaKuv) combines Transformer parallelization (training) with RNN efficiency (inference). Installation : Basic usage (GPT mode + RNN mode): Common workflows Workflow 1: Text generation (streaming) Efficient token by token generation : Key advantage : Constant memory per token (no growing KV cache) Workflow 2: Long context processing (infinite context) Process million token sequences : Workflow 3: Fine tuning RWKV Standard fine tuning workflow : Workflow 4: RWKV vs Transformer comparison Memory comparison (1M token sequence): Speed comparison (inference): When to use vs alternatives Use RWKV when : Need very long context (100K+ tokens) Want …
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