Stable Diffusion 1.5 — Text to Image (basic) txt2img

The canonical starter graph: load a checkpoint, encode a positive + negative prompt, KSample, decode, save. Swap in any SD1.5 checkpoint.

Models: v1-5-pruned-emaonly.safetensors (or any SD1.5 checkpoint) · 7 nodes

{
  "3": {
    "class_type": "KSampler",
    "inputs": {
      "seed": 0,
      "steps": 20,
      "cfg": 7,
      "sampler_name": "euler",
      "scheduler": "normal",
      "denoise": 1,
      "model": [
        "4",
        0
      ],
      "positive": [
        "6",
        0
      ],
      "negative": [
        "7",
        0
      ],
      "latent_image": [
        "5",
        0
      ]
    }
  },
  "4": {
    "class_type": "CheckpointLoaderSimple",
    "inputs": {
      "ckpt_name": "v1-5-pruned-emaonly.safetensors"
    }
  },
  "5": {
    "class_type": "EmptyLatentImage",
    "inputs": {
      "width": 512,
      "height": 512,
      "batch_size": 1
    }
  },
  "6": {
    "class_type": "CLIPTextEncode",
    "inputs": {
      "text": "a majestic Egyptian temple at golden hour, cinematic, highly detailed",
      "clip": [
        "4",
        1
      ]
    }
  },
  "7": {
    "class_type": "CLIPTextEncode",
    "inputs": {
      "text": "blurry, low quality, watermark, text",
      "clip": [
        "4",
        1
      ]
    }
  },
  "8": {
    "class_type": "VAEDecode",
    "inputs": {
      "samples": [
        "3",
        0
      ],
      "vae": [
        "4",
        2
      ]
    }
  },
  "9": {
    "class_type": "SaveImage",
    "inputs": {
      "filename_prefix": "MELEK",
      "images": [
        "8",
        0
      ]
    }
  }
}