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Update link in deterministic blog (#207)
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blog/2025-09-22-sglang-deterministic.md

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@@ -160,7 +160,7 @@ Attention kernel is an important part of determinism. For different attention ba
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### Reproducible Non-Greedy Sampling
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To extend determinism beyond greedy decoding, we introduce a new sampling function: [multinomial_with_seed](https://github.com/sgl-project/sglang/blob/fb1e8acd2954b6267c73a199427976d89887ff0e/python/sglang/srt/layers/sampler.py#L263).
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To extend determinism beyond greedy decoding, we introduce a new sampling function: [multinomial_with_seed](https://github.com/sgl-project/sglang/blob/e2ac7888b8cb1fd6c33a7ec58d27a5f5b5b24e0c/python/sglang/srt/layers/sampler.py#L268-L299).
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Instead of relying on `torch.multinomial`, which is inherently nondeterministic under batching, this operator perturbs logits with Gumbel noise generated from a **seeded hash function**. As a result, the same `(inputs, seed)` pair always yields the same sample, even when temperature > 0.
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