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A comment on DeepScaleR: Surpassing O1-Preview with a 1.5B Model by Scaling RL. Parent comment
say you have a tool:
def calculator(expr: str) -> float
then the model just needs to say:
{ "function": "calculator", "args": { "expr": "5 + 10" } }
then in your code you can easily pass that to the "calculator" function and get the result, then hand the result back to the model. Making it feel like the model can "call" an external function.
deep seek can also do this: https://www.boundaryml.com/blog/deepseek-r1-function-calling
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say you have a tool:
def calculator(expr: str) -> float
then the model just needs to say:
{ "function": "calculator", "args": { "expr": "5 + 10" } }
then in your code you can easily pass that to the "calculator" function and get the result, then hand the result back to the model. Making it feel like the model can "call" an external function.
deep seek can also do this: https://www.boundaryml.com/blog/deepseek-r1-function-calling