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the traces you already log are training data - keep the runs that did the task well, fine-tune a small model on them, eval on your task a 9B model beating frontier models makes sense when it's trained on exactly your task smithtune: https://langchain.com/blog/langsmith-fin…
.@corridor used smithtune’s trace-based workflow to build the training data for Argos, a fine-tuned 9B model that scores the highest of the 14 models they tested on their security context benchmark. 🧵 Full thread ⤵️ https://t.co/eOkWzNZnJL