I wanted to start a broader setup showcase thread around Open Source AI.
A useful angle is performance, but it also connects with future improvements. 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 Open Source AI is genuinely useful and where it still needs improvement.
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A useful angle is performance, but it also connects with future improvements. 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 Open Source AI is genuinely useful and where it still needs improvement.
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