工作流 /
角色与时尚 /
LTX-2.3 IC-LoRA：参考生视频
LTX-2.3 IC-LoRA：参考生视频
LTX-2.3 IC-LoRA: Reference Sheet Control
生成与参考图清单（包含角色、道具和地点）视觉一致的短视频CLIP。输入复合参考图和描述动作的分割提示词，输出单个视频CLIP。适用于角色驱动动画、一致的道具可视化和特定场景生成。
角色与时尚
13 个节点 1 个输入 112 次使用 ComfyUI ≥ 0.22.0 ComfyUI 101 KB
需要的权重
这个工作流引用了 4 个权重文件，其中 3 个能在本站模型库里找到。
gemma-3-12b-it-abliterated_lora_rank64_bf16.safetensors
在模型库查看
gemma_3_12B_it_fp4_mixed.safetensors
在模型库查看
ltx-2.3-22b-distilled-fp8.safetensors
模型库暂未收录
ltx-2.3-22b-ic-lora-ingredients-0.9.safetensors
在模型库查看
节点构成
MarkdownNote
× 2
PrimitiveInt
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SaveVideo
× 1
f9f61b10-b689-4d67-b4fa-0acc1d9b5390
× 1
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× 1
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× 1
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× 1
GetImageSize
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× 1
PreviewImage
× 1
LoadImage
× 1
官方标注的模型
LTX-2.3
工作流 JSON
和上面「下载工作流 JSON」是同一份文件。
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83 "- Hugging Face (base): [Lightricks/LTX-2.3](https://huggingface.co/Lightricks/LTX-2.3/)\n- Hugging Face (Ingredients IC-LoRA): [Lightricks/LTX-2.3-22b-IC-LoRA-Ingredients](https://huggingface.co/Comfy-Org/ltx-2.3/resolve/main/split_files/loras/ltx-2.3-22b-ic-lora-ingredients-0.9.safetensors) (1.22 GB)\n- [gemma-3-12b-it-abliterated_lora_rank64_bf16.safetensors](https://huggingface.co/Comfy-Org/ltx-2/resolve/main/split_files/loras/gemma-3-12b-it-abliterated_lora_rank64_bf16.safetensors) (599.1 MB)\n\n\n## Model Storage Location\n\n- [Hugging Face:Comfy-Org/ltx-2.3](https://huggingface.co/Comfy-Org/ltx-2.3)\n- [ModelScope:Comfy-Org/ltx-2.3](https://modelscope.cn/models/Comfy-Org/ltx-2.3)\n- [Hugging Face:Comfy-Org/ltx-2](https://huggingface.co/Comfy-Org/ltx-2)\n- [ModelScope:Comfy-Org/ltx-2](https://modelscope.cn/models/Comfy-Org/ltx-2)\n\n```\n📂 ComfyUI/\n├── 📂 models/\n│ ├── 📂 checkpoints/\n│ │ └── ltx-2.3-22b-distilled-fp8.safetensors\n│ ├── 📂 text_encoders/\n│ │ └── gemma_3_12B_it_fp4_mixed.safetensors\n│ └── 📂 loras/\n│ ├── ltx-2.3-22b-ic-lora-ingredients-0.9.safetensors\n│ └── gemma-3-12b-it-abliterated_lora_rank64_bf16.safetensors\n```\n\n## Report Issue\n\nNote: Please update ComfyUI first ([guide](https://docs.comfy.org/installation/update_comfyui)) and prepare required models. Desktop/Cloud updates follow stable releases, so some nightly-supported models may not be available yet.\n\n- Cannot run / runtime errors: [ComfyUI/issues](https://github.com/comfyanonymous/ComfyUI/issues)\n- UI / frontend issues: [ComfyUI_frontend/issues](https://github.com/Comfy-Org/ComfyUI_frontend/issues)\n- Workflow issues: [workflow_templates/issues](https://github.com/Comfy-Org/workflow_templates/issues)\n"
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328 "## IC-LoRA Ingredients\n\nSources (official only):\n- Model card: [Lightricks/LTX-2.3-22b-IC-LoRA-Ingredients](https://huggingface.co/Lightricks/LTX-2.3-22b-IC-LoRA-Ingredients)\n- IC-LoRA docs: [docs.ltx.video — IC-LoRA usage guide](https://docs.ltx.video/open-source-model/usage-guides/ic-lo-ra)\n\n### What This Model Is\nFrom the model card:\n\n> This is an IC-LoRA trained on top of LTX-2.3-22B, which conditions video generation on a reference sheet — a single composite image inventorying the characters, props, and location of a scene — so that generated videos keep those elements visually consistent.\n\n\n**Model details (model card):**\n- Base Model: LTX-2.3-22B (dev)\n- Training Type: IC-LoRA (in-context LoRA)\n- Control Type: Reference-sheet conditioning — character / prop / location identity carried into the generated video\n- Reference Downscale Factor: `1` (the reference is provided at the same resolution as the output)\n- Pipeline: the reference sheet is supplied as a static video (the still sheet looped to the output's length and frame rate). Trained with a `video_to_video` strategy over reference latents; no extra color/space transforms are applied at inference.\n\n### Intended Use & Out-of-Scope\nFrom the model card:\n\n- **Intended use:** Generating short video clips that stay faithful to a supplied reference sheet — keeping recurring characters (face and costume), handled props, and the set/location consistent with the sheet while following an action described in the prompt.\n- **Out of scope:** This is not a general text-to-video model — it expects a reference sheet as conditioning. It was trained at a single resolution / length bucket (**768×448**, **121 frames**, **24 fps**); other resolutions, much longer clips, or use without a reference sheet are out of distribution. It does not reproduce identities that are absent from the supplied sheet.\n\n### Control Signal Requirements\nFrom the model card:\n\n- **Control signal type:** Reference sheet — a single composite image with one clean panel per distinct visual element (each character as a face close-up + body turnaround, each prop as a product-style render, and one clean location panel), laid out on a **black background with no text**.\n- **Expected input:** A static video built from the reference sheet, looped to match the output clip's length and frame rate, at the output resolution (downscale factor 1).\n- **Preprocessing:** Author the reference sheet, then loop the still into a static video. Frame count must be **≥ 121** so the reference-encoding / 121-frame read bucket is satisfied; all targets in training were ≥ 121 frames.\n- **Alignment:** The reference video should match the output resolution and frame rate; its frame count must be at least the output length (clamped to ≥ 121).\n\n### Prompt Format\nFrom the model card — the prompt is split into two labeled parts, matching how the model was trained:\n\n```text\nReference sheet: <description of the panels in the sheet — characters, props, location>\n\nGenerated video: <description of the action / shot you want generated>\n```\n\nAt inference, the reference sheet (as a static video) supplies *what things look like*, and the `Generated video:` portion supplies *what happens*. The model reads the reference latents in-context and renders a new clip whose characters, props, and setting match the sheet.\n\nModel-card gallery examples also show prompts labeled as `### Reference Sheet Description` / `### Target Description`.\n\n### ComfyUI Usage\nFrom the model card:\n\n1. Copy the LoRA weights into `models/loras`.\n2. Load the LTX-2.3-22B base model and add the Ingredients LoRA.\n3. Start at strength `1.0` and adjust to taste.\n4. Use an IC-LoRA / reference workflow from the LTX-2 ComfyUI repository, which already wires the reference (control) input. Connect the reference-sheet static video as the control/reference input; a generic LoRA loader that ignores the reference path will not apply the conditioning.\n\n### Recommended Settings\nFrom the model card:\n\n- LoRA strength / weight: **1.4**\n- Inference steps: **30**\n- Guidance scale: **4.0**\n- Resolution & frames: **768×448**, **121 frames**, **24 fps** (the trained bucket — best results here)\n- Prompting: use the two-part `Reference sheet: … / Generated video: …` structure. The `Reference sheet:` text should describe the panels present; the `Generated video:` text drives the action.\n- Suggested negative prompt: `worst quality, inconsistent motion, blurry, jittery, distorted`\n- Validation used spatiotemporal guidance (STG, mode `stg_v`, block 29, scale 1.0), which can help motion stability.\n\n### Tips & Troubleshooting\nFrom the model card only:\n\n- **Bigger panels carry over better:** The more space an element takes up in the reference image, the more faithfully it carries over into the generated video. Give important characters/props larger, more prominent panels rather than small or crowded ones.\n- **Identity drift:** If a character's face or costume drifts, make sure the reference sheet has a clean, front-facing close-up and full turnaround for that character, and that its panel isn't cluttered or text-laden.\n- **Element not appearing:** The model only reproduces elements present on the sheet — add a dedicated panel for any prop/character you need to persist, and describe it in the `Reference sheet:` portion of the prompt.\n- **Reference too short:** The reference static video must be ≥ 121 frames; shorter references break the reference-encoding bucket.\n"
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