I wanted to start a broader workflow comparison thread around Model Training & Fine-Tuning.
A useful angle is prompt design, but it also connects with common mistakes. 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 Model Training & Fine-Tuning is genuinely useful and where it still needs improvement.

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A useful angle is prompt design, but it also connects with common mistakes. 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 Model Training & Fine-Tuning is genuinely useful and where it still needs improvement.

Photo by on