Prediction
fofr/sd3-explorer:7c48d3a1Input
- 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
- triple_prompt_clip_g
- triple_prompt_clip_l
- negative_conditioning_end
- 0
- triple_prompt_empty_padding
{
"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
}
npm install replicate
REPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
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
}
}
);
console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
REPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
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.
REPLICATE_API_TOKEN
environment variableexport 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": "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.
brew install cog
If you don’t have Homebrew, there are other installation options available.
Pull and run fofr/sd3-explorer using Cog (this will download the full 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.
Pull and run fofr/sd3-explorer using Docker (this will download the full 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
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"
}
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