fofr/sd3-explorer:7c48d3a1 – Run with an API on Replicate

Version

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fofr /sd3-explorer:7c48d3a1

Input

prompt

string

Shift + Return to add a new line

a man and woman are standing together against a backdrop, the backdrop is divided equally in half down the middle, left side is red, right side is gold, the woman is wearing a t-shirt with a yoda motif, she has a long skirt with birds on it, the man is wearing a three piece purple suit, he has spiky blue haira man and woman are standing together against a backdrop, the backdrop is divided equally in half down the middle, left side is red, right side is gold, the woman is wearing a t-shirt with a yoda motif, she has a long skirt with birds on it, the man is wearing a three piece purple suit, he has spiky blue hair

This prompt is ignored when using the triple prompt mode. See below.

Default: ""

model

string

An enumeration.

Default: "sd3_medium_incl_clips_t5xxlfp16.safetensors"

width

integer

The width of the image

Default: 1024

height

integer

The height of the image

Default: 1024

steps

integer

The number of steps to run the diffusion model for

Default: 28

sampler

string

The sampler to use for the diffusion model

Default: "dpmpp_2m"

scheduler

string

The scheduler to use for the diffusion model

Default: "sgm_uniform"

shift

number

(minimum: 0, maximum: 20)

The timestep scheduling shift. Try values 6.0 and 2.0 to experiment with effects.

Default: 3

guidance_scale

number

(minimum: 0, maximum: 20)

The guidance scale tells the model how similar the output should be to the prompt.

Default: 4.5

number_of_images

integer

(minimum: 1, maximum: 10)

The number of images to generate

Default: 1

use_triple_prompt

boolean

Default: false

triple_prompt_clip_g

string

Shift + Return to add a new line

The prompt that will be passed to just the CLIP-G model.

Default: ""

triple_prompt_clip_l

string

Shift + Return to add a new line

The prompt that will be passed to just the CLIP-L model.

Default: ""

triple_prompt_t5

string

Shift + Return to add a new line

The prompt that will be passed to just the T5-XXL model.

Default: ""

triple_prompt_empty_padding

boolean

Whether to add padding for empty prompts. Useful if you only want to pass a prompt to one or two of the three text encoders. Has no effect when all prompts are filled. Disable this for interesting effects.

Default: true

negative_prompt

string

Shift + Return to add a new line

Negative prompts do not really work in SD3. This will simply cause your output image to vary in unpredictable ways.

Default: ""

negative_conditioning_end

number

(minimum: 0, maximum: 20)

When the negative conditioning should stop being applied. By default it is disabled.

Default: 0

output_format

string

Format of the output images

Default: "webp"

output_quality

integer

(minimum: 0, maximum: 100)

Quality of the output images, from 0 to 100. 100 is best quality, 0 is lowest quality.

Default: 80

seed

integer

Set a seed for reproducibility. Random by default.

Run this model in Node.js with one line of code:

npx create-replicate --model=fofr/sd3-explorer

or set up a project from scratch

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run fofr/sd3-explorer using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "fofr/sd3-explorer:7c48d3a1f9e16683c3f1e546056becfe31b963a872384458703f7aa6a40a2c69",
  {
    input: {
      model: "sd3_medium_incl_clips_t5xxlfp16.safetensors",
      shift: 3,
      steps: 28,
      width: 1024,
      height: 1024,
      prompt: "a man and woman are standing together against a backdrop, the backdrop is divided equally in half down the middle, left side is red, right side is gold, the woman is wearing a t-shirt with a yoda motif, she has a long skirt with birds on it, the man is wearing a three piece purple suit, he has spiky blue hair",
      sampler: "dpmpp_2m",
      scheduler: "sgm_uniform",
      output_format: "webp",
      guidance_scale: 4.5,
      output_quality: 80,
      negative_prompt: "",
      number_of_images: 1,
      triple_prompt_t5: "",
      use_triple_prompt: false,
      triple_prompt_clip_g: "",
      triple_prompt_clip_l: "",
      negative_conditioning_end: 0,
      triple_prompt_empty_padding: true
    }
  }
);

// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output[0]);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run fofr/sd3-explorer using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "fofr/sd3-explorer:7c48d3a1f9e16683c3f1e546056becfe31b963a872384458703f7aa6a40a2c69",
    input={
        "model": "sd3_medium_incl_clips_t5xxlfp16.safetensors",
        "shift": 3,
        "steps": 28,
        "width": 1024,
        "height": 1024,
        "prompt": "a man and woman are standing together against a backdrop, the backdrop is divided equally in half down the middle, left side is red, right side is gold, the woman is wearing a t-shirt with a yoda motif, she has a long skirt with birds on it, the man is wearing a three piece purple suit, he has spiky blue hair",
        "sampler": "dpmpp_2m",
        "scheduler": "sgm_uniform",
        "output_format": "webp",
        "guidance_scale": 4.5,
        "output_quality": 80,
        "negative_prompt": "",
        "number_of_images": 1,
        "triple_prompt_t5": "",
        "use_triple_prompt": False,
        "triple_prompt_clip_g": "",
        "triple_prompt_clip_l": "",
        "negative_conditioning_end": 0,
        "triple_prompt_empty_padding": True
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Run fofr/sd3-explorer using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "fofr/sd3-explorer:7c48d3a1f9e16683c3f1e546056becfe31b963a872384458703f7aa6a40a2c69",
    "input": {
      "model": "sd3_medium_incl_clips_t5xxlfp16.safetensors",
      "shift": 3,
      "steps": 28,
      "width": 1024,
      "height": 1024,
      "prompt": "a man and woman are standing together against a backdrop, the backdrop is divided equally in half down the middle, left side is red, right side is gold, the woman is wearing a t-shirt with a yoda motif, she has a long skirt with birds on it, the man is wearing a three piece purple suit, he has spiky blue hair",
      "sampler": "dpmpp_2m",
      "scheduler": "sgm_uniform",
      "output_format": "webp",
      "guidance_scale": 4.5,
      "output_quality": 80,
      "negative_prompt": "",
      "number_of_images": 1,
      "triple_prompt_t5": "",
      "use_triple_prompt": false,
      "triple_prompt_clip_g": "",
      "triple_prompt_clip_l": "",
      "negative_conditioning_end": 0,
      "triple_prompt_empty_padding": true
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

You can run this model locally using Cog. First, install Cog:

brew install cog

If you don’t have Homebrew, there are other installation options available.

Run this to download the model and run it in your local environment:

cog predict r8.im/fofr/sd3-explorer@sha256:7c48d3a1f9e16683c3f1e546056becfe31b963a872384458703f7aa6a40a2c69 \
  -i 'model="sd3_medium_incl_clips_t5xxlfp16.safetensors"' \
  -i 'shift=3' \
  -i 'steps=28' \
  -i 'width=1024' \
  -i 'height=1024' \
  -i 'prompt="a man and woman are standing together against a backdrop, the backdrop is divided equally in half down the middle, left side is red, right side is gold, the woman is wearing a t-shirt with a yoda motif, she has a long skirt with birds on it, the man is wearing a three piece purple suit, he has spiky blue hair"' \
  -i 'sampler="dpmpp_2m"' \
  -i 'scheduler="sgm_uniform"' \
  -i 'output_format="webp"' \
  -i 'guidance_scale=4.5' \
  -i 'output_quality=80' \
  -i 'negative_prompt=""' \
  -i 'number_of_images=1' \
  -i 'triple_prompt_t5=""' \
  -i 'use_triple_prompt=false' \
  -i 'triple_prompt_clip_g=""' \
  -i 'triple_prompt_clip_l=""' \
  -i 'negative_conditioning_end=0' \
  -i 'triple_prompt_empty_padding=true'

To learn more, take a look at the Cog documentation.

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 --gpus=all r8.im/fofr/sd3-explorer@sha256:7c48d3a1f9e16683c3f1e546056becfe31b963a872384458703f7aa6a40a2c69
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "model": "sd3_medium_incl_clips_t5xxlfp16.safetensors",
      "shift": 3,
      "steps": 28,
      "width": 1024,
      "height": 1024,
      "prompt": "a man and woman are standing together against a backdrop, the backdrop is divided equally in half down the middle, left side is red, right side is gold, the woman is wearing a t-shirt with a yoda motif, she has a long skirt with birds on it, the man is wearing a three piece purple suit, he has spiky blue hair",
      "sampler": "dpmpp_2m",
      "scheduler": "sgm_uniform",
      "output_format": "webp",
      "guidance_scale": 4.5,
      "output_quality": 80,
      "negative_prompt": "",
      "number_of_images": 1,
      "triple_prompt_t5": "",
      "use_triple_prompt": false,
      "triple_prompt_clip_g": "",
      "triple_prompt_clip_l": "",
      "negative_conditioning_end": 0,
      "triple_prompt_empty_padding": true
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

{
  "completed_at": "2024-06-18T11:59:23.602030Z",
  "created_at": "2024-06-18T11:59:14.919000Z",
  "data_removed": false,
  "error": null,
  "id": "z78h5v1dwxrgp0cg5cvrpgs2fc",
  "input": {
    "model": "sd3_medium_incl_clips_t5xxlfp16.safetensors",
    "shift": 3,
    "steps": 28,
    "width": 1024,
    "height": 1024,
    "prompt": "a man and woman are standing together against a backdrop, the backdrop is divided equally in half down the middle, left side is red, right side is gold, the woman is wearing a t-shirt with a yoda motif, she has a long skirt with birds on it, the man is wearing a three piece purple suit, he has spiky blue hair",
    "sampler": "dpmpp_2m",
    "scheduler": "sgm_uniform",
    "output_format": "webp",
    "guidance_scale": 4.5,
    "output_quality": 80,
    "negative_prompt": "",
    "number_of_images": 1,
    "triple_prompt_t5": "",
    "use_triple_prompt": false,
    "triple_prompt_clip_g": "",
    "triple_prompt_clip_l": "",
    "negative_conditioning_end": 0,
    "triple_prompt_empty_padding": true
  },
  "logs": "Random seed set to: 2483966773\nRunning workflow\ngot prompt\nExecuting node 6, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode\nExecuting node 271, title: KSampler, class type: KSampler\n  0%|          | 0/28 [00:00<?, ?it/s]\n  4%|▎         | 1/28 [00:00<00:04,  5.89it/s]\n  7%|▋         | 2/28 [00:00<00:06,  3.93it/s]\n 11%|█         | 3/28 [00:00<00:06,  4.09it/s]\n 14%|█▍        | 4/28 [00:00<00:05,  4.15it/s]\n 18%|█▊        | 5/28 [00:01<00:05,  4.18it/s]\n 21%|██▏       | 6/28 [00:01<00:05,  4.22it/s]\n 25%|██▌       | 7/28 [00:01<00:04,  4.24it/s]\n 29%|██▊       | 8/28 [00:01<00:04,  4.25it/s]\n 32%|███▏      | 9/28 [00:02<00:04,  4.25it/s]\n 36%|███▌      | 10/28 [00:02<00:04,  4.26it/s]\n 39%|███▉      | 11/28 [00:02<00:03,  4.26it/s]\n 43%|████▎     | 12/28 [00:02<00:03,  4.26it/s]\n 46%|████▋     | 13/28 [00:03<00:03,  4.26it/s]\n 50%|█████     | 14/28 [00:03<00:03,  4.26it/s]\n 54%|█████▎    | 15/28 [00:03<00:03,  4.26it/s]\n 57%|█████▋    | 16/28 [00:03<00:02,  4.26it/s]\n 61%|██████    | 17/28 [00:03<00:02,  4.26it/s]\n 64%|██████▍   | 18/28 [00:04<00:02,  4.26it/s]\n 68%|██████▊   | 19/28 [00:04<00:02,  4.25it/s]\n 71%|███████▏  | 20/28 [00:04<00:01,  4.26it/s]\n 75%|███████▌  | 21/28 [00:04<00:01,  4.26it/s]\n 79%|███████▊  | 22/28 [00:05<00:01,  4.25it/s]\n 82%|████████▏ | 23/28 [00:05<00:01,  4.25it/s]\n 86%|████████▌ | 24/28 [00:05<00:00,  4.25it/s]\n 89%|████████▉ | 25/28 [00:05<00:00,  4.25it/s]\n 93%|█████████▎| 26/28 [00:06<00:00,  4.25it/s]\n 96%|█████████▋| 27/28 [00:06<00:00,  4.25it/s]\n100%|██████████| 28/28 [00:06<00:00,  4.24it/s]\n100%|██████████| 28/28 [00:06<00:00,  4.25it/s]\nExecuting node 231, title: VAE Decode, class type: VAEDecode\nExecuting node 273, title: Save Image, class type: SaveImage\nPrompt executed in 7.17 seconds\noutputs:  {'273': {'images': [{'filename': 'SD3_00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nSD3_00001_.png",
  "metrics": {
    "predict_time": 8.645392249,
    "total_time": 8.68303
  },
  "output": [
    "https://replicate.delivery/pbxt/BnkJxF51oYZsBdGsgn6vGIkeQUO17GgTPloJCuM0LpQNR5fSA/SD3_00001_.webp"
  ],
  "started_at": "2024-06-18T11:59:14.956637Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/z78h5v1dwxrgp0cg5cvrpgs2fc",
    "cancel": "https://api.replicate.com/v1/predictions/z78h5v1dwxrgp0cg5cvrpgs2fc/cancel"
  },
  "version": "7c48d3a1f9e16683c3f1e546056becfe31b963a872384458703f7aa6a40a2c69"
}

Generated in

8.7 seconds

Tweak it ShareReport

Random seed set to: 2483966773
Running workflow
got prompt
Executing node 6, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode
Executing node 271, title: KSampler, class type: KSampler
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Executing node 231, title: VAE Decode, class type: VAEDecode
Executing node 273, title: Save Image, class type: SaveImage
Prompt executed in 7.17 seconds
outputs:  {'273': {'images': [{'filename': 'SD3_00001_.png', 'subfolder': '', 'type': 'output'}]}}
====================================
SD3_00001_.png