MOSS-Image-SFT-DeBand / tools /moss_image_t2i_api.json
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{
"1": {
"class_type": "UNETLoader",
"inputs": {
"unet_name": "moss_image_sft_bf16.safetensors",
"weight_dtype": "default"
}
},
"30": {
"class_type": "LoraLoaderModelOnly",
"inputs": {
"model": [
"1",
0
],
"lora_name": "moss_image_sft_lora_blocks_21_to_49_rank_512_bf16.safetensors",
"strength_model": -0.5
}
},
"16": {
"class_type": "TemporalScoreRescaling",
"inputs": {
"model": [
"30",
0
],
"tsr_k": 0.95,
"tsr_sigma": 1.0
}
},
"2": {
"class_type": "SkipLayerGuidanceDiTSimple",
"inputs": {
"model": [
"16",
0
],
"double_layers": "",
"single_layers": "22, 24",
"start_percent": 0.1,
"end_percent": 0.7
}
},
"3": {
"class_type": "CLIPLoader",
"inputs": {
"clip_name": "qwen3.5_9b_int8_convrot.safetensors",
"type": "moss_image",
"device": "default"
}
},
"4": {
"class_type": "VAELoader",
"inputs": {
"vae_name": "flux2-vae.safetensors"
}
},
"18": {
"class_type": "PrimitiveStringMultiline",
"inputs": {
"value": "You turn a user's image idea into one detailed caption for a text-to-image model. The model learned from captions that describe finished images, so write the caption as a description of the image itself, not as instructions.\n\nKeep the request\n- Keep everything the user specified: subjects, counts, actions, relationships, medium, style, mood, colors and anything they excluded. Never contradict or drop it.\n- Fill in what they left open with concrete visual choices: setting, composition and framing, viewpoint, lighting, materials and textures, color palette, and the artistic medium.\n- Describe only what can be seen. Leave out sounds, smells, backstory and intentions.\n- Do not invent real-world facts the user did not give, such as specific dates, prices, names or specifications.\n\nText in the image\n- Quote every piece of visible text exactly, in double quotes. Keep the user's wording, language, spelling, capitalization, punctuation and line breaks; never translate it.\n- If the user asks for a designed image (poster, cover, menu, label, sign, infographic) without giving its text, write short, specific copy that fits instead of placeholders.\n- Describe where each text sits and how it looks: position, reading order, alignment, line breaks, relative size, font style, color and spacing.\n- Do not mention watermarks or artist signatures.\n\nWriting\n- Write in English, in plain prose: one to three paragraphs, usually 80 to 200 words, longer only when there is a lot of text to place.\n- Open with the medium and the main subject, then the setting and composition, then lighting, colors and finer details.\n- Give positions with words such as left, right, top, bottom, foreground and background. No coordinates, lists, headings, JSON or Markdown.\n- No quality keywords such as \"masterpiece\", \"best quality\", \"8k\" or \"highly detailed\", and no negative prompt.\n\nReply with the caption only: no title, introduction, explanation or surrounding quotes.\n"
}
},
"17": {
"class_type": "TextGenerate",
"inputs": {
"clip": [
"3",
0
],
"prompt": "",
"max_length": 4096,
"sampling_mode": "on",
"sampling_mode.temperature": 0.7,
"sampling_mode.top_k": 64,
"sampling_mode.top_p": 0.95,
"sampling_mode.min_p": 0.05,
"sampling_mode.repetition_penalty": 1.05,
"sampling_mode.seed": 0,
"thinking": false,
"use_default_template": true,
"mtp": "auto",
"system_prompt": [
"18",
0
]
}
},
"19": {
"class_type": "PreviewAny",
"inputs": {
"source": [
"17",
0
]
}
},
"5": {
"class_type": "CLIPTextEncode",
"inputs": {
"clip": [
"3",
0
],
"text": [
"17",
0
]
}
},
"6": {
"class_type": "CLIPTextEncode",
"inputs": {
"clip": [
"3",
0
],
"text": "worst quality, bad anatomy, watermark, jpeg artifact"
}
},
"7": {
"class_type": "EmptyFlux2LatentImage",
"inputs": {
"width": 1024,
"height": 1024,
"batch_size": 1
}
},
"21": {
"class_type": "SamplerER_SDE",
"inputs": {
"solver_type": "ER-SDE",
"max_stage": 3,
"eta": 1.0,
"s_noise": 1.05
}
},
"22": {
"class_type": "BasicScheduler",
"inputs": {
"model": [
"2",
0
],
"scheduler": "simple",
"steps": 25,
"denoise": 1.0
}
},
"20": {
"class_type": "SamplerCustom",
"inputs": {
"model": [
"2",
0
],
"add_noise": true,
"noise_seed": 16,
"cfg": 3.0,
"positive": [
"5",
0
],
"negative": [
"6",
0
],
"sampler": [
"21",
0
],
"sigmas": [
"22",
0
],
"latent_image": [
"7",
0
]
}
},
"9": {
"class_type": "VAEDecode",
"inputs": {
"samples": [
"20",
0
],
"vae": [
"4",
0
]
}
},
"10": {
"class_type": "SaveImage",
"inputs": {
"images": [
"9",
0
],
"filename_prefix": "moss/moss"
}
}
}