The 22B distilled DiT was trained against ltx_core's fixed DISTILLED_SIGMA_VALUES, but the diffusers scheduler derives 8-step spacing from resolution-shifted flow matching and lands far off at every reachable mu (second sigma 0.945-0.981 vs 0.99375, tail 0.37-0.61 -> 0.1 vs 0.725 -> 0.42 -> 0). At the distilled default step count the backend now passes the list verbatim, neutralising the scheduler's dynamic shift and terminal stretch for the call (they distort even explicit sigmas) and restoring them afterwards. Other step counts and the dev/base DiT keep the scheduler's own spacing. Live-verified on B200: the scheduler holds the exact curve after an 8-step distilled GGUF generation, config restored, healthy clip. Also reword the transformer_quant resolved reason to the measured reality: quant halves resident weights and hosted checkpoints cut load time, while per-step speed is roughly bf16 parity. |
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| .. | ||
| backend | ||
| frontend | ||
| src-tauri | ||
| __init__.py | ||
| install_llama_prebuilt.py | ||
| install_node_prebuilt.py | ||
| install_python_stack.py | ||
| install_sd_cpp_prebuilt.py | ||
| LICENSE.AGPL-3.0 | ||
| node_prebuilt_pins.json | ||
| package-lock.json | ||
| package.json | ||
| setup.bat | ||
| setup.ps1 | ||
| setup.sh | ||
| Unsloth_Studio_Colab.ipynb | ||