Fixing Tool-Call Accuracy in vLLM

(ubicloud.com)

55 points | by coffeemug 1 hour ago

7 comments

  • creativeSlumber 1 minute ago
    Can the same mechanism be used to make sure it outputs syntactically correct code?
  • jesdo 1 hour ago
    I'm one of the authors of this blog post. Figuring out how to integrate the LLM, the inference and serving engine, and the constrained decoding implementation such that you get the intended output and overall quality definitely requires careful engineering and testing. Please feel free to AMA. :)
    • ivanjermakov 56 minutes ago
      Do you know where <||> syntax is coming from? I find it very odd that existing markup wasn't used and there is very little info online about it.
      • jesdo 43 minutes ago
        To the LLM, the <|...|> tags are single, special tokens. They are rendered as <|...|> tags for readability, but to the model the tags are single tokens.

        I do not know why these tokens are visualized as <|...|>, but I speculate that this way they are easily recognizable as special-purpose tokens, and difficult to confuse with other types of existing markup.

        • zahlman 13 minutes ago
          So to be clear, you can't prompt-inject these?

          ... How did they get into the training data?

      • t_mahmood 49 minutes ago
        Correct me if I wrong, I saw this when llama.cpp or ollama initializes, it is used as token separator of some sort.
        • cowlevel 45 minutes ago
          GPT-2 used <|endoftext|>
  • sroussey 33 minutes ago
    Constrained decoding came to JS land transformers last month for in browser structured output as well, also used for tool calling.

    https://github.com/huggingface/transformers.js/blob/main/pac...

  • sarmedshafi 50 minutes ago
    [flagged]
  • arbor-group 56 minutes ago
    [flagged]
  • michaelpo 52 minutes ago
    [dead]
  • fr2029r 34 minutes ago
    [dead]