Training: LoRA, AV-LoRA, and IC-LoRA
- →Name the four real training modes and pick the right one for a stated goal
- →Explain what IC-LoRA actually is and reject the identity-conditioning myth
- →Prepare a dataset that satisfies the resolution and frame-count constraints before a run starts
- →Size and budget a training run against the documented hardware tiers
Training is where the fabrication problem in the LTX ecosystem is worst, because training advice is expensive to check. A wrong endpoint fails in two seconds; a wrong training plan fails after you have rented a GPU for eight hours. Two myths in particular have propagated widely enough that they show up in AI coding assistants' output. Both are corrected here before anything else.
ltx-trainer is not on PyPI. Unlike ltx-core and ltx-pipelines, you use it from inside a clone of the Lightricks/LTX-2 monorepo, driven by uv:
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The 5-lesson Foundation module is free and always will be — you have already read the part most guides get wrong. The paid lessons go deeper, with labs, knowledge checks, and every technical claim verified against live documentation.
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