Non-determinism in GPT-4 is caused by Sparse MoE - 152334H
It’s well-known at this point that GPT-4/GPT-3.5-turbo is non-deterministic, even at temperature=0.0. This is an odd behavior if you’re used to dense decoder-only models, where temp=0 should imply greedy sampling which should imply full determinism, because the logits for the next token should be a pure function of the input sequence & the model weights.
Non-determinism in GPT-4 is caused by Sparse MoE What the title says 152334H included in Tech August 5, 2023 1701 words 8 minutes Contents It's well-known at this point that GPT-4/GPT-3.5-turbo is non-deterministic, even at temperature=0.0 . This is an odd behavior if you're used to dense decoder-only models, where temp=0 should imply greedy sampling which should imply full determinism, because the logits for the next token should be a pure function of the input sequence & the model weights. When asked about this behaviour at the developer roundtables during OpenAI's World Tour, the responses
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related reading
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- GitHub - brexhq/prompt-engineering: Tips and tricks for working with Large Language Models like OpenAI's GPT-4.github.com
- Non-Determinism of “Deterministic” LLM Settingsarxiv.org
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- gpt-4-system-card.pdfcdn.openai.com
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