Failed to load versions. Head to the versions page to see all versions for this model.
You're looking at a specific version of this model. Jump to the model overview.
lucataco /stable-diffusion-3.5-large-lora:ad0f061a
Input
Run this model in Node.js with one line of code:
npm install replicate
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
import Replicate from "replicate";
import fs from "node:fs";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});
Run lucataco/stable-diffusion-3.5-large-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"lucataco/stable-diffusion-3.5-large-lora:ad0f061aaf2813ff8dbdba3613a952fca0bf443ef0ddd3ef500d66046ce97c23",
{
input: {
prompt: "Frog, yarn art style",
hf_lora: "https://huggingface.co/lucataco/SD3.5-Large-yarn-2/resolve/main/pytorch_lora_weights.safetensors",
lora_scale: 1,
aspect_ratio: "1:1",
output_format: "webp",
guidance_scale: 4.5,
output_quality: 80,
prompt_strength: 0.7,
num_inference_steps: 28
}
}
);
// 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.
pip install replicate
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
import replicate
Run lucataco/stable-diffusion-3.5-large-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"lucataco/stable-diffusion-3.5-large-lora:ad0f061aaf2813ff8dbdba3613a952fca0bf443ef0ddd3ef500d66046ce97c23",
input={
"prompt": "Frog, yarn art style",
"hf_lora": "https://huggingface.co/lucataco/SD3.5-Large-yarn-2/resolve/main/pytorch_lora_weights.safetensors",
"lora_scale": 1,
"aspect_ratio": "1:1",
"output_format": "webp",
"guidance_scale": 4.5,
"output_quality": 80,
"prompt_strength": 0.7,
"num_inference_steps": 28
}
)
print(output)
To learn more, take a look at the guide on getting started with Python.
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run lucataco/stable-diffusion-3.5-large-lora 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": "lucataco/stable-diffusion-3.5-large-lora:ad0f061aaf2813ff8dbdba3613a952fca0bf443ef0ddd3ef500d66046ce97c23",
"input": {
"prompt": "Frog, yarn art style",
"hf_lora": "https://huggingface.co/lucataco/SD3.5-Large-yarn-2/resolve/main/pytorch_lora_weights.safetensors",
"lora_scale": 1,
"aspect_ratio": "1:1",
"output_format": "webp",
"guidance_scale": 4.5,
"output_quality": 80,
"prompt_strength": 0.7,
"num_inference_steps": 28
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Add a payment method to run this model.
By signing in, you agree to our
terms of service and privacy policy
Output
{
"completed_at": "2024-11-01T19:42:00.762609Z",
"created_at": "2024-11-01T19:41:46.730000Z",
"data_removed": false,
"error": null,
"id": "arhvz2w3d9rj00cjx4zvv42b78",
"input": {
"prompt": "Frog, yarn art style",
"hf_lora": "https://huggingface.co/lucataco/SD3.5-Large-yarn-2/resolve/main/pytorch_lora_weights.safetensors",
"lora_scale": 1,
"aspect_ratio": "1:1",
"output_format": "webp",
"guidance_scale": 4.5,
"output_quality": 80,
"prompt_strength": 0.7,
"num_inference_steps": 28
},
"logs": "Using seed: 52957\nPrompt: Frog, yarn art style\ntxt2img mode\nLoading LoRA took: 0.00 seconds\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:13, 2.08it/s]\n 7%|▋ | 2/28 [00:00<00:10, 2.44it/s]\n 11%|█ | 3/28 [00:01<00:11, 2.26it/s]\n 14%|█▍ | 4/28 [00:01<00:11, 2.18it/s]\n 18%|█▊ | 5/28 [00:02<00:10, 2.14it/s]\n 21%|██▏ | 6/28 [00:02<00:10, 2.11it/s]\n 25%|██▌ | 7/28 [00:03<00:10, 2.10it/s]\n 29%|██▊ | 8/28 [00:03<00:09, 2.09it/s]\n 32%|███▏ | 9/28 [00:04<00:09, 2.08it/s]\n 36%|███▌ | 10/28 [00:04<00:08, 2.08it/s]\n 39%|███▉ | 11/28 [00:05<00:08, 2.07it/s]\n 43%|████▎ | 12/28 [00:05<00:07, 2.07it/s]\n 46%|████▋ | 13/28 [00:06<00:07, 2.07it/s]\n 50%|█████ | 14/28 [00:06<00:06, 2.07it/s]\n 54%|█████▎ | 15/28 [00:07<00:06, 2.07it/s]\n 57%|█████▋ | 16/28 [00:07<00:05, 2.07it/s]\n 61%|██████ | 17/28 [00:08<00:05, 2.06it/s]\n 64%|██████▍ | 18/28 [00:08<00:04, 2.06it/s]\n 68%|██████▊ | 19/28 [00:09<00:04, 2.06it/s]\n 71%|███████▏ | 20/28 [00:09<00:03, 2.06it/s]\n 75%|███████▌ | 21/28 [00:10<00:03, 2.06it/s]\n 79%|███████▊ | 22/28 [00:10<00:02, 2.06it/s]\n 82%|████████▏ | 23/28 [00:11<00:02, 2.06it/s]\n 86%|████████▌ | 24/28 [00:11<00:01, 2.06it/s]\n 89%|████████▉ | 25/28 [00:11<00:01, 2.06it/s]\n 93%|█████████▎| 26/28 [00:12<00:00, 2.06it/s]\n 96%|█████████▋| 27/28 [00:12<00:00, 2.06it/s]\n100%|██████████| 28/28 [00:13<00:00, 2.06it/s]\n100%|██████████| 28/28 [00:13<00:00, 2.08it/s]",
"metrics": {
"predict_time": 14.022834929,
"total_time": 14.032609
},
"output": [
"https://replicate.delivery/yhqm/WKTZ1ZnQRYZ4H9nYCfNwL34ZfGeTLkg7iBemxmIAeoXDhwldC/out-0.webp"
],
"started_at": "2024-11-01T19:41:46.739774Z",
"status": "succeeded",
"urls": {
"stream": "https://stream.replicate.com/v1/files/qoxq-forjqxshlyxo5w4dt65casntzgirel5pym6b5kl3vasfgbanbh3q",
"get": "https://api.replicate.com/v1/predictions/arhvz2w3d9rj00cjx4zvv42b78",
"cancel": "https://api.replicate.com/v1/predictions/arhvz2w3d9rj00cjx4zvv42b78/cancel"
},
"version": "ad0f061aaf2813ff8dbdba3613a952fca0bf443ef0ddd3ef500d66046ce97c23"
}
Using seed: 52957
Prompt: Frog, yarn art style
txt2img mode
Loading LoRA took: 0.00 seconds
0%| | 0/28 [00:00<?, ?it/s]
4%|▎ | 1/28 [00:00<00:13, 2.08it/s]
7%|▋ | 2/28 [00:00<00:10, 2.44it/s]
11%|█ | 3/28 [00:01<00:11, 2.26it/s]
14%|█▍ | 4/28 [00:01<00:11, 2.18it/s]
18%|█▊ | 5/28 [00:02<00:10, 2.14it/s]
21%|██▏ | 6/28 [00:02<00:10, 2.11it/s]
25%|██▌ | 7/28 [00:03<00:10, 2.10it/s]
29%|██▊ | 8/28 [00:03<00:09, 2.09it/s]
32%|███▏ | 9/28 [00:04<00:09, 2.08it/s]
36%|███▌ | 10/28 [00:04<00:08, 2.08it/s]
39%|███▉ | 11/28 [00:05<00:08, 2.07it/s]
43%|████▎ | 12/28 [00:05<00:07, 2.07it/s]
46%|████▋ | 13/28 [00:06<00:07, 2.07it/s]
50%|█████ | 14/28 [00:06<00:06, 2.07it/s]
54%|█████▎ | 15/28 [00:07<00:06, 2.07it/s]
57%|█████▋ | 16/28 [00:07<00:05, 2.07it/s]
61%|██████ | 17/28 [00:08<00:05, 2.06it/s]
64%|██████▍ | 18/28 [00:08<00:04, 2.06it/s]
68%|██████▊ | 19/28 [00:09<00:04, 2.06it/s]
71%|███████▏ | 20/28 [00:09<00:03, 2.06it/s]
75%|███████▌ | 21/28 [00:10<00:03, 2.06it/s]
79%|███████▊ | 22/28 [00:10<00:02, 2.06it/s]
82%|████████▏ | 23/28 [00:11<00:02, 2.06it/s]
86%|████████▌ | 24/28 [00:11<00:01, 2.06it/s]
89%|████████▉ | 25/28 [00:11<00:01, 2.06it/s]
93%|█████████▎| 26/28 [00:12<00:00, 2.06it/s]
96%|█████████▋| 27/28 [00:12<00:00, 2.06it/s]
100%|██████████| 28/28 [00:13<00:00, 2.06it/s]
100%|██████████| 28/28 [00:13<00:00, 2.08it/s]