Keep special sampling params #1186
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WoosukKwon
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Sep 26, 2023
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@blahblahasdf Thanks for the PR! Can you change it to skip_special_tokens? I think this will improve the compatibility with HF.
Yup will do. |
WoosukKwon
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Sep 28, 2023
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please note this will lead to P sampled first token not equal to D sampled first token. <!--- pyml disable-next-line no-emphasis-as-heading -->
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See the discussion on #970
I have a model that generates special tokens with important meaning to generation tasks. At present there is no way to get these special tokens back in the generated text because of the hardcoded input to detokenize_incrementally in llm_engine.
This PR adds an optional parameter to
SamplingParams