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For Pika, it helps to think in terms of inputs, constraints, verification, and iteration. One important area is setup choices. Define what a good result looks like before changing tools or settings, then test one variable at a time so you can tell what actually improved the outcome. Another...

A practical understanding of Llama Models starts with knowing what the system does well, where it is unreliable, and how to validate the result. One important area is advanced workflows. Define what a good result looks like before changing tools or settings, then test one variable at a time so...