I wanted to start a broader mistakes and lessons thread around Llama Models.
A useful angle is cost control, but it also connects with data quality. Different tools and workflows can produce very different results even when the goal is similar.
It would be interesting to compare practical examples, experiments, setups, or lessons that show where Llama Models is genuinely useful and where it still needs improvement.
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A useful angle is cost control, but it also connects with data quality. Different tools and workflows can produce very different results even when the goal is similar.
It would be interesting to compare practical examples, experiments, setups, or lessons that show where Llama Models is genuinely useful and where it still needs improvement.
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