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* server: spec checkpoints for recurrent models * fix: save/restore sampler state during speculative checkpoint When speculative decoding rejects draft tokens and restores the recurrent state checkpoint, the sampler (RNG, grammar, prev tokens) must also be restored to maintain consistency. Without this, the sampler state reflects the rejected draft tokens, leading to potential divergence. Uses common_sampler_clone() to snapshot the sampler before the speculative batch decode, and restores it on rejection. * server: snapshot recurrent state in tensor * reset ngram mod state for rejected tokens * server: refactor checkpoint state logic * speculative: fix sampler for checkpoints * recurrent model: implement recurrent kernel checkpoint * recurrent model: refactor api * spec: free rbudget before overwriting
180 KiB
180 KiB