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joyanujoy /analog_diffusion:eff6035c
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 joyanujoy/analog_diffusion using Replicateβs API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"joyanujoy/analog_diffusion:eff6035c43836061271808afa1d8ed256e603043489093a9b35bfee9cfe53e48",
{
input: {
width: 512,
height: 512,
prompt: "analog style photo of a man",
upscale: 2,
lora_urls: "",
scheduler: "DPMSolverMultistep",
lora_scales: "0.5",
num_outputs: 1,
adapter_type: "sketch",
guidance_scale: 7.5,
negative_prompt: "",
prompt_strength: 0.8,
verbose_response: false,
clip_interrogator: true,
remove_background: false,
num_inference_steps: 50
}
}
);
// 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 joyanujoy/analog_diffusion using Replicateβs API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"joyanujoy/analog_diffusion:eff6035c43836061271808afa1d8ed256e603043489093a9b35bfee9cfe53e48",
input={
"width": 512,
"height": 512,
"prompt": "analog style photo of a man",
"upscale": 2,
"lora_urls": "",
"scheduler": "DPMSolverMultistep",
"lora_scales": "0.5",
"num_outputs": 1,
"adapter_type": "sketch",
"guidance_scale": 7.5,
"negative_prompt": "",
"prompt_strength": 0.8,
"verbose_response": False,
"clip_interrogator": True,
"remove_background": False,
"num_inference_steps": 50
}
)
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 joyanujoy/analog_diffusion using Replicateβs 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": "joyanujoy/analog_diffusion:eff6035c43836061271808afa1d8ed256e603043489093a9b35bfee9cfe53e48",
"input": {
"width": 512,
"height": 512,
"prompt": "analog style photo of a man",
"upscale": 2,
"lora_urls": "",
"scheduler": "DPMSolverMultistep",
"lora_scales": "0.5",
"num_outputs": 1,
"adapter_type": "sketch",
"guidance_scale": 7.5,
"negative_prompt": "",
"prompt_strength": 0.8,
"verbose_response": false,
"clip_interrogator": true,
"remove_background": false,
"num_inference_steps": 50
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicateβs HTTP API reference docs.
Add a payment method to run this model.
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Output
{
"completed_at": "2023-03-23T18:30:55.965066Z",
"created_at": "2023-03-23T18:28:19.794684Z",
"data_removed": false,
"error": null,
"id": "csascvfyijbt3pjmvrfhfyvrja",
"input": {
"width": 512,
"height": 512,
"prompt": "analog style photo of a man",
"scheduler": "DPMSolverMultistep",
"lora_scales": "0.5",
"num_outputs": 1,
"adapter_type": "sketch",
"guidance_scale": 7.5,
"prompt_strength": 0.8,
"clip_interrogator": true,
"remove_background": false,
"num_inference_steps": 50
},
"logs": "Using seed: 55601\nGenerating image of 512 x 512 with prompt: analog style photo of a man\nNo LoRA models provided, using default model...\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|β | 1/50 [00:01<01:34, 1.93s/it]\n 6%|β | 3/50 [00:02<00:26, 1.78it/s]\n 10%|β | 5/50 [00:02<00:14, 3.19it/s]\n 14%|ββ | 7/50 [00:02<00:09, 4.69it/s]\n 18%|ββ | 9/50 [00:02<00:06, 6.07it/s]\n 22%|βββ | 11/50 [00:02<00:05, 7.35it/s]\n 26%|βββ | 13/50 [00:02<00:04, 8.57it/s]\n 30%|βββ | 15/50 [00:03<00:03, 9.66it/s]\n 34%|ββββ | 17/50 [00:03<00:03, 10.59it/s]\n 38%|ββββ | 19/50 [00:03<00:02, 11.20it/s]\n 42%|βββββ | 21/50 [00:03<00:02, 11.42it/s]\n 46%|βββββ | 23/50 [00:03<00:02, 11.58it/s]\n 50%|βββββ | 25/50 [00:03<00:02, 11.88it/s]\n 54%|ββββββ | 27/50 [00:04<00:01, 11.91it/s]\n 58%|ββββββ | 29/50 [00:04<00:01, 12.21it/s]\n 62%|βββββββ | 31/50 [00:04<00:01, 12.08it/s]\n 66%|βββββββ | 33/50 [00:04<00:01, 12.26it/s]\n 70%|βββββββ | 35/50 [00:04<00:01, 12.02it/s]\n 74%|ββββββββ | 37/50 [00:04<00:01, 12.33it/s]\n 78%|ββββββββ | 39/50 [00:04<00:00, 12.19it/s]\n 82%|βββββββββ | 41/50 [00:05<00:00, 12.07it/s]\n 86%|βββββββββ | 43/50 [00:05<00:00, 12.31it/s]\n 90%|βββββββββ | 45/50 [00:05<00:00, 12.61it/s]\n 94%|ββββββββββ| 47/50 [00:05<00:00, 12.44it/s]\n 98%|ββββββββββ| 49/50 [00:05<00:00, 13.00it/s]\n100%|ββββββββββ| 50/50 [00:05<00:00, 8.56it/s]",
"metrics": {
"predict_time": 7.81628,
"total_time": 156.170382
},
"output": [
"https://replicate.delivery/pbxt/0iNkiPzqlGbvHpKLkdDga7q6FWd2gZeKNVj71G2ibltvZSVIA/out-0.png"
],
"started_at": "2023-03-23T18:30:48.148786Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/csascvfyijbt3pjmvrfhfyvrja",
"cancel": "https://api.replicate.com/v1/predictions/csascvfyijbt3pjmvrfhfyvrja/cancel"
},
"version": "eff6035c43836061271808afa1d8ed256e603043489093a9b35bfee9cfe53e48"
}
Using seed: 55601
Generating image of 512 x 512 with prompt: analog style photo of a man
No LoRA models provided, using default model...
0%| | 0/50 [00:00<?, ?it/s]
2%|β | 1/50 [00:01<01:34, 1.93s/it]
6%|β | 3/50 [00:02<00:26, 1.78it/s]
10%|β | 5/50 [00:02<00:14, 3.19it/s]
14%|ββ | 7/50 [00:02<00:09, 4.69it/s]
18%|ββ | 9/50 [00:02<00:06, 6.07it/s]
22%|βββ | 11/50 [00:02<00:05, 7.35it/s]
26%|βββ | 13/50 [00:02<00:04, 8.57it/s]
30%|βββ | 15/50 [00:03<00:03, 9.66it/s]
34%|ββββ | 17/50 [00:03<00:03, 10.59it/s]
38%|ββββ | 19/50 [00:03<00:02, 11.20it/s]
42%|βββββ | 21/50 [00:03<00:02, 11.42it/s]
46%|βββββ | 23/50 [00:03<00:02, 11.58it/s]
50%|βββββ | 25/50 [00:03<00:02, 11.88it/s]
54%|ββββββ | 27/50 [00:04<00:01, 11.91it/s]
58%|ββββββ | 29/50 [00:04<00:01, 12.21it/s]
62%|βββββββ | 31/50 [00:04<00:01, 12.08it/s]
66%|βββββββ | 33/50 [00:04<00:01, 12.26it/s]
70%|βββββββ | 35/50 [00:04<00:01, 12.02it/s]
74%|ββββββββ | 37/50 [00:04<00:01, 12.33it/s]
78%|ββββββββ | 39/50 [00:04<00:00, 12.19it/s]
82%|βββββββββ | 41/50 [00:05<00:00, 12.07it/s]
86%|βββββββββ | 43/50 [00:05<00:00, 12.31it/s]
90%|βββββββββ | 45/50 [00:05<00:00, 12.61it/s]
94%|ββββββββββ| 47/50 [00:05<00:00, 12.44it/s]
98%|ββββββββββ| 49/50 [00:05<00:00, 13.00it/s]
100%|ββββββββββ| 50/50 [00:05<00:00, 8.56it/s]