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Add 沙雕动画角色

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+ ═══════════════════════════════════════════════════════════════════════════════
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+ 沙雕动画角色
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+ ═══════════════════════════════════════════════════════════════════════════════
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+
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+ ───────────────────────────────────────────────────────────────────────────────
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+ IDENTITY
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+ ───────────────────────────────────────────────────────────────────────────────
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+ Base model LTX-2.3
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+ Generation mode not declared by the author
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+ Checkpoint not determined — verify before use
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+ Category Visual style
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+ Author updatemp
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+ Source https://civitai.com/models/2146978
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+ Provenance CivitAI · model 2146978 · version 2835214
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+
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+ ───────────────────────────────────────────────────────────────────────────────
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+ WEIGHTS
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+ ───────────────────────────────────────────────────────────────────────────────
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+ File LTX2.3-沙雕动画.safetensors
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+ Version LTX-2.3-沙雕动画角色
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+ Size 643.0 MB
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+ Format SafeTensor / unknown precision
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+ SHA256 a8d176991003cf847b0d06ea2a4caae15ed8259649f491b52f0014c44159fd97
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+ Published 2026-04-06
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+
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+ ───────────────────────────────────────────────────────────────────────────────
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+ TRIGGER WORDS
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+ ───────────────────────────────────────────────────────────────────────────────
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+ › "shadiaodonghua"
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+
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+ ───────────────────────────────────────────────────────────────────────────────
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+ RECOMMENDED SETTINGS
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+ ───────────────────────────────────────────────────────────────────────────────
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+ The author did not publish specific settings.
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+ No author settings were published. Community baseline: steps Distilled path
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+ (all six official ComfyUI LTX-2.3 templates): 8 steps in stage 1 driven by
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+ an explicit ManualSigmas list "1.0, 0.99375, 0.9875, 0.98125, 0.975,
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+ 0.909375, 0.725, 0.421875, 0.0", then 3 steps in the stage-2 refine after
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+ the x2 latent upscale ("0.85, 0.7250, 0.4219, 0.0") — verified by reading
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+ the template JSONs. The ic_lora template instead uses a plain KSampler at 8
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+ steps. The Python DistilledPipeline is documented as "8 predefined sigmas
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+ (8 steps in stage 1, 4 steps in stage 2)". Full/dev model with real
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+ guidance: Lightricks' own single-stage example workflow sets LTXVScheduler
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+ to 15 steps., cfg 1.0 for anything running the distilled checkpoint or the
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+ distilled LoRA — CFGGuider is set to 1 in both stages of every official
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+ ComfyUI template (verified in the JSONs), the ic_lora template's KSampler
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+ is cfg 1, and a note in Lightricks' own two- stage workflow reads "Do
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+ explore various samplers and cfg values (although we advise them to be kept
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+ close to 1)". For the guided full-model path, Lightricks' single-stage
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+ workflow uses MultimodalGuider with per-modality GuiderParameters: VIDEO
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+ cfg 3 (rescale 0.9), AUDIO cfg 7 (rescale 0.7). Treat 3 as the video anchor
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+ since that is the official value., sampler euler with SamplerCustomAdvanced
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+ + ManualSigmas is the default in the ComfyUI templates; the flf2v template
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+ uses SamplerEulerAncestral and the ic_lora template a plain KSampler with
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+ euler_ancestral + linear_quadratic. Lightricks' own example workflows use
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+ euler_ancestral_cfg_pp (single stage) and euler_cfg_pp (two stage).
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+ TI2VidTwoStagesHQPipeline swaps in the second-order res_2s sampler for
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+ fewer steps., resolution Generate low, then upscale. ComfyUI templates set
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+ EmptyLTXVLatentVideo to 768x512 / 97 frames and target 1280x720 (with a
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+ 1920x1088 resize and a 1536-long-edge resize in the chain), using
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+ LTXVLatentUpsampler with ltx-2.3-spatial- upscaler-x2-1.1.safetensors.
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+ Lightricks' own example workflows use 960x544 / 121 frames with the same x2
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+ upscaler. Hard constraints from the model card: width and height must be
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+ divisible by 32, and frame count must be divisible by 8 plus 1 (97, 121,
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+ 193...). Frame rate: LTXVConditioning is 24 in the t2v/id_lora templates
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+ and 25 in the ic_lora/flf2v templates; CreateVideo is 24 in the ComfyUI
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+ templates. The x2 temporal upscaler is described in the model card as being
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+ for higher FPS., lora_strength Official distilled/acceleration LoRA: 0.5 in
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+ every ComfyUI template (LoraLoaderModelOnly), 0.5 plus a 0.2 second branch
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+ in Lightricks' single- stage example workflow, and 0.8 in the ltx-pipelines
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+ README/installation CLI example (--distilled-lora <path> 0.8). Official IC-
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+ LoRA Union-Control and ID-LoRA: 1.0 in the templates. Community norm for
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+ content/style LoRAs: the IC-LoRA Dual-Character author states 0.6-1.0 used
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+ alone, dropped to 0.3-0.5 when stacked with other LoRAs..
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+
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+ ───────────────────────────────────────────────────────────────────────────────
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+ ADOPTION & POPULARITY
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+ ───────────────────────────────────────────────────────────────────────────────
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+ Downloads 737
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+ Rating 100% positive (64/64)
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+ Comments 3
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+ Published 152 days ago
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+ Download rate 0.7/day since release
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+
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+ Adoption rank #55 of 150 in this collection (Moderate)
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+ Momentum rank #143 of 150 by download rate (Long tail)
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+
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+ Adoption tier is the percentile of total downloads within this collection;
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+ momentum is the percentile of downloads-per-day since release. Momentum is
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+ ranked rather than measured against a fixed rate, because this base model
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+ is itself new and every LoRA looks fast on an absolute scale. Both numbers
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+ are CivitAI's, read on the scrape date at the foot of this file.
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+
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+ ───────────────────────────────────────────────────────────────────────────────
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+ CHAINING / STACKING
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+ ───────────────────────────────────────────────────────────────────────────────
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+ Stacks with others not stated
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+
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+ The author gave no chaining guidance. The rules below are the
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+ general LTX-2.3 ones, not anything specific to this LoRA.
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+
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+ General LTX-2.3 rules that apply here (see REFERENCE.txt):
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+
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+ • Stacking an acceleration LoRA with a task LoRA is officially
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+ sanctioned: the ID-LoRA template chains LoraLoaderModelOnly(ltx_2.3_22b
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+ _distilled_1.1_lora_dynamic_fro09_avg_rank_111_bf16, 0.5) into
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+ LoraLoaderModelOnly(ltx-2.3-id-lora-talkvid-3k, 1.0) on the dev
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+ checkpoint.
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+ • The Python CLI exposes `--lora <path> [strength]` as a repeatable flag
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+ with default strength 1.0, so multiple adapters at once is a supported
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+ configuration, not a hack.
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+ • Load the acceleration/distilled LoRA on the dev checkpoint only. The
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+ two-stage pipelines require it for the full model but explicitly do not
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+ use it for DistilledPipeline, ICLoraPipeline or DubItPipeline, which
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+ already run distilled weights.
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+ • Do not stack two distillation LoRAs (e.g. the official rank-384 /
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+ rank-111 one plus a community DMD LoRA). The DaSiWa DMD LoRA already
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+ blends 75-80% of the official distilled delta into its audio-output
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+ route and is described by its author as recreating the distilled model
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+ on top of stock dev, i.e. a replacement.
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+ • IC-LoRAs are not chained like ordinary LoRAs: each carries a
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+ reference_downscale_factor in its safetensors metadata and needs a node
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+ that reads it (GetICLoRAParameters -> LTXVAddGuide in core, or
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+ LTXICLoRALoaderModelOnly + LTXAddVideoICLoRAGuide in ComfyUI-LTXVideo).
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+ Without one the factor silently defaults to 1.
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+ • Two IC-LoRA reference guides can be driven from a single IC-LoRA: the
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+ CrossView Warp author wires both a depth-warp video and the original
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+ video into separate reference guides and sets latent_downscale_factor =
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+ 1 on both.
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+ • DubItPipeline accepts exactly one Dub-It IC-LoRA (`--lora` exactly
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+ once) and applies it in both stages — that path is single-adapter by
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+ design.
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+ • Community convention on strengths when stacking: the IC-LoRA Dual-
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+ Character author recommends 0.6-1.0 for a content LoRA used alone,
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+ dropped to 0.3-0.5 when combined with others.
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+ • Some LoRA pairs are designed to be blended against each other — the LTX
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+ 2.3 Crisp Enhance / Soft Enhance pair is described by its author as
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+ "can be used together and balanced at different strengths".
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+ • The gemma-3-12b-it-abliterated LoRA is not a video LoRA and does not
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+ belong in the DiT chain — it patches the Gemma text encoder through a
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+ model+clip LoraLoader, as the official templates wire it.
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+ • The author never states which weight family this targets. Within
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+ LTX-2.3, dev vs distilled is low risk: they are the same architecture
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+ and the distillation itself is published as a LoRA that the model card
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+ calls "applicable to the full model", so ordinary content LoRAs load on
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+ both. Expect style/strength drift rather than breakage; the
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+
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+ ───────────────────────────────────────────────────────────────────────────────
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+ PROS
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+ ───────────────────────────────────────────────────────────────────────────────
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+ + Positively received — 64 thumbs-up with no down-votes. [source: CivitAI
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+ stats]
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+ + Explicit trigger word(s) — shadiaodonghua — so the effect can be turned
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+ on and off from the prompt. [source: model metadata]
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+
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+ ───────────────────────────────────────────────────────────────────────────────
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+ CONS & CAVEATS
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+ ───────────────────────────────────────────────────────────────────────────────
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+ - Author never states which generation mode it was trained for; test
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+ against your own workflow before relying on it. [source: description]
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+ - Large at 643 MB — slower to load and heavier to stack. [source: file
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+ size]
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+ - Modest adoption (737 downloads) — less community feedback to rely on.
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+ [source: CivitAI stats]
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+
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+ ───────────────────────────────────────────────────────────────────────────────
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+ COMPATIBILITY WARNING
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+ ───────────────────────────────────────────────────────────────────────────────
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+ Within LTX-2.3, dev vs distilled is low risk: they are the same
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+ architecture and the distillation itself is published as a LoRA that the
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+ model card calls "applicable to the full model", so ordinary content LoRAs
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+ load on both. Expect style/strength drift rather than breakage; the
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+ distilled LoRA is meant to be applied to a dev checkpoint, not stacked on
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+ an already-distilled one (the Python pipelines that start from a distilled
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+ checkpoint — DistilledPipeline, ICLoraPipeline, DubItPipeline — explicitly
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+ do not take --distilled-lora). The genuine risk is cross-version and cross-
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+ format, and it is silent rather than a hard error: the LTX-2 repo README
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+ states flatly that files "are not interchangeable between the two models,
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+ and a LoRA only works with the model it was trained on", and a wrong-
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+ version LoRA surfaces only as a stream of "lora key not loaded:
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+ diffusion_model...." console warnings while generation proceeds as if no
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+ LoRA were attached. The same silent no-op hits correctly-versioned LoRAs
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+ saved in a non-ComfyUI key layout: SimpleTuner issue #2349 shows keys like
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+ diffusion_model.connectors.audio_connector.transformer_blocks.N.attn1.to_q
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+ going unloaded, where the LTX-2 trainer's own layout is attn1/attn2 for
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+ video, audio_attn1/audio_attn2 for audio and audio_to_video_attn /
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+ video_to_audio_attn for cross-modal. Community finetunes (Sulphur 2, JoyAI-
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+ Echo merges) load stock LTX-2.3 LoRAs but shift the result. And an IC-LoRA
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+ loaded without a metadata-reading node loses its reference scale: ComfyUI's
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+ GetICLoRAParameters reads reference_downscale_factor out of the LoRA's
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+ safetensors metadata and silently falls back to 1 when it is absent, so a
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+ ref0.5 IC-LoRA wired straight into LTXVAddGuide without it feeds the
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+ reference at the wrong latent scale.
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+
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+ ───────────────────────────────────────────────────────────────────────────────
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+ AUTHOR'S DESCRIPTION
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+ ───────────────────────────────────────────────��───────────────────────────────
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+ 一个沙雕动画角色的lora,我训练完跑图的时候才想起来,这200张训练集里居然没有虾仁...
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+ 不过现在看泛化倒是挺好的,训练集全部都是古装的服装,用gemini写的泛化提示词,自己试吧,效果还行。
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+
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+ Here is a LoRA for a goofy/meme-style anime character. I didn't realize
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+ until I started testing the model that I completely forgot to include any
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+ combat/killer poses (or 'shrimp', as we say in slang) in the 200-image
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+ training set...
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+ However, the generalization turned out to be surprisingly good. Even though
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+ the dataset consisted entirely of ancient Chinese costumes, I used Gemini
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+ to generate the variation prompts. Feel free to try it out yourself—the
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+ results are actually pretty solid.
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+
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+ ───────────────────────────────────────────────────────────────────────────────
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+ EXAMPLE MEDIA
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+ ───────────────────────────────────────────────────────────────────────────────
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+ 6 preview(s) in ./example_images/ — community results for
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+ this LoRA. Videos keep a matching _poster.jpg still frame.
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+
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+ No prompts are recorded below: CivitAI's public API flags these posts as
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+ having generation metadata but does not return it, so the prompts cannot be
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+ scraped. Open the model page to read them.
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+
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+ 01_video.mp4 (video, 1536x2048)
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+ still: 01_poster.jpg
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+ 02_video.mp4 (video, 1536x2048)
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+ still: 02_poster.jpg
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+ 03_video.mp4 (video, 1536x2048)
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+ still: 03_poster.jpg
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+ 04_video.mp4 (video, 1536x2048)
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+ still: 04_poster.jpg
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+ 05_video.mp4 (video, 1536x2048)
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+ still: 05_poster.jpg
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+ 06_video.mp4 (video, 1536x2048)
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+ still: 06_poster.jpg
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+
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+ ───────────────────────────────────────────────────────────────────────────────
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+ HOW TO USE (COMFYUI)
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+ ───────────────────────────────────────────────────────────────────────────────
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+ 1. Update ComfyUI. LTX-2.3 is supported in ComfyUI core
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+ (comfy_extras/nodes_lt.py provides EmptyLTXVLatentVideo, LTXVAddGuide,
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+ GetICLoRAParameters, LTXVConditioning, LTXVScheduler,
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+ LTXVConcatAVLatent/LTXVSeparateAVLatent, LTXVReferenceAudio and more) and
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+ the six official templates need no custom nodes; install the Lightricks
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+ "ComfyUI-LTXVideo" custom node pack only if you want IC-LoRA loaders, low-
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+ VRAM loaders, HDR decode, audio-only nodes or Q8 nodes.
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+ 2. Put the base checkpoint in ComfyUI/models/checkpoints/ —
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+ ltx-2.3-22b-dev-fp8.safetensors (29.15 GB) or ltx-2.3-22b-distilled-
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+ fp8.safetensors (29.53 GB) from Lightricks/LTX-2.3-fp8, or the bf16
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+ originals (46.15 GB) from Lightricks/LTX-2.3. It is a single file that also
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+ carries the video VAE, the audio VAE and the text projection.
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+ 3. Put gemma_3_12B_it_fp4_mixed.safetensors in
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+ ComfyUI/models/text_encoders/ (from Comfy-Org/ltx-2). The Python package
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+ instead wants the full google/gemma-3-12b-it-qat-q4_0-unquantized folder.
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+ 4. Put ltx-2.3-spatial-upscaler-x2-1.1.safetensors in
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+ ComfyUI/models/latent_upscale_models/ (needed by every two-stage template),
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+ and moge_2_vitl_normal_fp16.safetensors (Comfy-Org/MoGe) in
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+ ComfyUI/models/geometry_estimation/ if you use the IC-LoRA depth path.
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+ 5. Put every LoRA .safetensors in ComfyUI/models/loras/. Subfolders are
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+ fine — Lightricks' own workflows reference
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+ "ltxv/ltx2/ltx-2.3-22b-distilled-lora-384-1.1.safetensors".
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+ 6. Load a normal content/style LoRA with LoraLoaderModelOnly, wired between
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+ CheckpointLoaderSimple's MODEL output and the guider/sampler. In the stock
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+ templates you chain it after the distilled-LoRA loader. Use the full
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+ LoraLoader (model + clip) only for the gemma-3-12b-it-abliterated LoRA,
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+ which patches the Gemma text encoder rather than the video model.
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+ 7. On a dev checkpoint, also load the acceleration LoRA
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+ (ltx_2.3_22b_distilled_1.1_lora_dynamic_fro09_avg_rank_111_bf16.safetensors
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+ at 0.5) unless you intend to run the slow guided path.
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+ 8. For an IC-LoRA, the LoRA loader alone is not enough: either use
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+ LTXICLoRALoaderModelOnly + LTXAddVideoICLoRAGuide (ComfyUI-LTXVideo), or —
268
+ as the official ic_lora template does — feed the LoRA-loaded model through
269
+ core's GetICLoRAParameters into LTXVAddGuide, so the
270
+ reference_downscale_factor stored in the file's safetensors metadata is
271
+ read instead of defaulting to 1.
272
+ 9. Template Library > Video > any LTX-2.3 workflow gives you correct wiring
273
+ to start from; workflow JSONs are at Comfy-Org/workflow_templates/templates
274
+ /video_ltx2_3_{t2v,i2v,ia2v,flf2v,ic_lora,id_lora}.json and
275
+ Lightricks/ComfyUI-LTXVideo/example_workflows/2.3/.
276
+
277
+ ───────────────────────────────────────────────────────────────────────────────
278
+ Scraped by lorakit on 2026-09-04 23:17 UTC.
279
+ Stats and description are the author's; pros/cons are derived from the
280
+ evidence tagged beside each line.
281
+ ───────────────────────────────────────────────────────────────────────────────
untitled/metadata.json ADDED
@@ -0,0 +1,139 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "name": "沙雕动画角色",
3
+ "slug": "untitled",
4
+ "base_model": "LTX-2.3",
5
+ "media_type": "video",
6
+ "model_id": 2146978,
7
+ "version_id": 2835214,
8
+ "version_name": "LTX-2.3-沙雕动画角色",
9
+ "source": "civitai",
10
+ "url": "https://civitai.com/models/2146978",
11
+ "repo_id": null,
12
+ "file_path": null,
13
+ "author": "updatemp",
14
+ "category": {
15
+ "key": "style",
16
+ "label": "Visual style"
17
+ },
18
+ "modalities": [],
19
+ "primary_modality": "unspecified",
20
+ "checkpoint_family": "unknown",
21
+ "trigger_words": [
22
+ "shadiaodonghua"
23
+ ],
24
+ "recommended_settings": {},
25
+ "chaining": {
26
+ "author": {
27
+ "stacks": "not stated",
28
+ "notes": "",
29
+ "avoid": [],
30
+ "requires": [],
31
+ "order": "",
32
+ "strength": "",
33
+ "stated": false
34
+ },
35
+ "general_rules": [
36
+ "Stacking an acceleration LoRA with a task LoRA is officially sanctioned: the ID-LoRA template chains LoraLoaderModelOnly(ltx_2.3_22b_distilled_1.1_lora_dynamic_fro09_avg_rank_111_bf16, 0.5) into LoraLoaderModelOnly(ltx-2.3-id-lora-talkvid-3k, 1.0) on the dev checkpoint.",
37
+ "The Python CLI exposes `--lora <path> [strength]` as a repeatable flag with default strength 1.0, so multiple adapters at once is a supported configuration, not a hack.",
38
+ "Load the acceleration/distilled LoRA on the dev checkpoint only. The two-stage pipelines require it for the full model but explicitly do not use it for DistilledPipeline, ICLoraPipeline or DubItPipeline, which already run distilled weights.",
39
+ "Do not stack two distillation LoRAs (e.g. the official rank-384 / rank-111 one plus a community DMD LoRA). The DaSiWa DMD LoRA already blends 75-80% of the official distilled delta into its audio-output route and is described by its author as recreating the distilled model on top of stock dev, i.e. a replacement.",
40
+ "IC-LoRAs are not chained like ordinary LoRAs: each carries a reference_downscale_factor in its safetensors metadata and needs a node that reads it (GetICLoRAParameters -> LTXVAddGuide in core, or LTXICLoRALoaderModelOnly + LTXAddVideoICLoRAGuide in ComfyUI-LTXVideo). Without one the factor silently defaults to 1.",
41
+ "Two IC-LoRA reference guides can be driven from a single IC-LoRA: the CrossView Warp author wires both a depth-warp video and the original video into separate reference guides and sets latent_downscale_factor = 1 on both.",
42
+ "DubItPipeline accepts exactly one Dub-It IC-LoRA (`--lora` exactly once) and applies it in both stages — that path is single-adapter by design.",
43
+ "Community convention on strengths when stacking: the IC-LoRA Dual-Character author recommends 0.6-1.0 for a content LoRA used alone, dropped to 0.3-0.5 when combined with others.",
44
+ "Some LoRA pairs are designed to be blended against each other — the LTX 2.3 Crisp Enhance / Soft Enhance pair is described by its author as \"can be used together and balanced at different strengths\".",
45
+ "The gemma-3-12b-it-abliterated LoRA is not a video LoRA and does not belong in the DiT chain — it patches the Gemma text encoder through a model+clip LoraLoader, as the official templates wire it.",
46
+ "The author never states which weight family this targets. Within LTX-2.3, dev vs distilled is low risk: they are the same architecture and the distillation itself is published as a LoRA that the model card calls \"applicable to the full model\", so ordinary content LoRAs load on both. Expect style/strength drift rather than breakage; the"
47
+ ]
48
+ },
49
+ "pros": [
50
+ "Positively received — 64 thumbs-up with no down-votes. [source: CivitAI stats]",
51
+ "Explicit trigger word(s) — shadiaodonghua — so the effect can be turned on and off from the prompt. [source: model metadata]"
52
+ ],
53
+ "cons": [
54
+ "Author never states which generation mode it was trained for; test against your own workflow before relying on it. [source: description]",
55
+ "Large at 643 MB — slower to load and heavier to stack. [source: file size]",
56
+ "Modest adoption (737 downloads) — less community feedback to rely on. [source: CivitAI stats]"
57
+ ],
58
+ "file": {
59
+ "name": "LTX2.3-沙雕动画.safetensors",
60
+ "size_bytes": 674249600,
61
+ "size_mb": 643.01,
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+ "sha256": "a8d176991003cf847b0d06ea2a4caae15ed8259649f491b52f0014c44159fd97"
63
+ },
64
+ "stats": {
65
+ "downloads": 737,
66
+ "thumbs_up": 64,
67
+ "thumbs_down": 0
68
+ },
69
+ "popularity": {
70
+ "downloads": 737,
71
+ "thumbs_up": 64,
72
+ "thumbs_down": 0,
73
+ "comments": 3,
74
+ "approval": "100% positive (64/64)",
75
+ "age_days": 151.6,
76
+ "downloads_per_day": 0.71,
77
+ "rank_by_downloads": 55,
78
+ "rank_by_momentum": 143,
79
+ "of_total": 150,
80
+ "adoption_tier": "Moderate",
81
+ "momentum": "Long tail"
82
+ },
83
+ "selection_score": 1905.0,
84
+ "selection_reasons": [
85
+ "737 downloads",
86
+ "64 thumbs-up",
87
+ "documented triggers + usage notes",
88
+ "top-ranked for its category"
89
+ ],
90
+ "example_media": [
91
+ {
92
+ "file": "01_video.mp4",
93
+ "type": "video",
94
+ "resolution": "1536x2048",
95
+ "prompt": "",
96
+ "poster": "01_poster.jpg"
97
+ },
98
+ {
99
+ "file": "02_video.mp4",
100
+ "type": "video",
101
+ "resolution": "1536x2048",
102
+ "prompt": "",
103
+ "poster": "02_poster.jpg"
104
+ },
105
+ {
106
+ "file": "03_video.mp4",
107
+ "type": "video",
108
+ "resolution": "1536x2048",
109
+ "prompt": "",
110
+ "poster": "03_poster.jpg"
111
+ },
112
+ {
113
+ "file": "04_video.mp4",
114
+ "type": "video",
115
+ "resolution": "1536x2048",
116
+ "prompt": "",
117
+ "poster": "04_poster.jpg"
118
+ },
119
+ {
120
+ "file": "05_video.mp4",
121
+ "type": "video",
122
+ "resolution": "1536x2048",
123
+ "prompt": "",
124
+ "poster": "05_poster.jpg"
125
+ },
126
+ {
127
+ "file": "06_video.mp4",
128
+ "type": "video",
129
+ "resolution": "1536x2048",
130
+ "prompt": "",
131
+ "poster": "06_poster.jpg"
132
+ }
133
+ ],
134
+ "tags": [
135
+ "base model"
136
+ ],
137
+ "scraped_at": "2026-09-04T23:17:07+00:00",
138
+ "path": "ltxv-2.3/untitled"
139
+ }