Readme
This model doesn't have a readme.
Lora of myself
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";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});
Run juddisjudd/ckh-flux-model using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"juddisjudd/ckh-flux-model:cb1df38ccb4fd273f4a7731931372f567a11bf839cc95743aba67b15a668a5c7",
{
input: {
model: "dev",
width: 512,
height: 512,
prompt: "a photo of ckh a man with a beard, realistic photo taken in a vinyl record store",
go_fast: false,
lora_scale: 1,
megapixels: "1",
num_outputs: 4,
aspect_ratio: "1:1",
output_format: "png",
guidance_scale: 3.5,
output_quality: 100,
prompt_strength: 0.8,
extra_lora_scale: 0.8,
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 juddisjudd/ckh-flux-model using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"juddisjudd/ckh-flux-model:cb1df38ccb4fd273f4a7731931372f567a11bf839cc95743aba67b15a668a5c7",
input={
"model": "dev",
"width": 512,
"height": 512,
"prompt": "a photo of ckh a man with a beard, realistic photo taken in a vinyl record store",
"go_fast": False,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 4,
"aspect_ratio": "1:1",
"output_format": "png",
"guidance_scale": 3.5,
"output_quality": 100,
"prompt_strength": 0.8,
"extra_lora_scale": 0.8,
"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 juddisjudd/ckh-flux-model 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": "cb1df38ccb4fd273f4a7731931372f567a11bf839cc95743aba67b15a668a5c7",
"input": {
"model": "dev",
"width": 512,
"height": 512,
"prompt": "a photo of ckh a man with a beard, realistic photo taken in a vinyl record store",
"go_fast": false,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 4,
"aspect_ratio": "1:1",
"output_format": "png",
"guidance_scale": 3.5,
"output_quality": 100,
"prompt_strength": 0.8,
"extra_lora_scale": 0.8,
"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
{
"completed_at": "2024-08-29T06:07:28.686559Z",
"created_at": "2024-08-29T06:06:46.215000Z",
"data_removed": false,
"error": null,
"id": "1wcbwktsrxrm40chkjz9722ga4",
"input": {
"model": "dev",
"width": 512,
"height": 512,
"prompt": "a photo of ckh a man with a beard, realistic photo taken in a vinyl record store",
"lora_scale": 1,
"num_outputs": 4,
"aspect_ratio": "1:1",
"output_format": "png",
"guidance_scale": 3.5,
"output_quality": 100,
"extra_lora_scale": 0.8,
"num_inference_steps": 28
},
"logs": "Using seed: 47241\nPrompt: a photo of ckh a man with a beard, realistic photo taken in a vinyl record store\ntxt2img mode\nUsing dev model\nfree=9521626193920\nDownloading weights\n2024-08-29T06:06:46Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpb44_ivbj/weights url=https://replicate.delivery/yhqm/i4w5exJOYelkEEghRYXIXTxTEfAup2GFIC5jt48dWo9a5uumA/trained_model.tar\n2024-08-29T06:06:48Z | INFO | [ Complete ] dest=/tmp/tmpb44_ivbj/weights size=\"172 MB\" total_elapsed=2.530s url=https://replicate.delivery/yhqm/i4w5exJOYelkEEghRYXIXTxTEfAup2GFIC5jt48dWo9a5uumA/trained_model.tar\nDownloaded weights in 2.56s\nLoaded LoRAs in 11.42s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:26, 1.00it/s]\n 7%|▋ | 2/28 [00:01<00:22, 1.15it/s]\n 11%|█ | 3/28 [00:02<00:23, 1.08it/s]\n 14%|█▍ | 4/28 [00:03<00:22, 1.04it/s]\n 18%|█▊ | 5/28 [00:04<00:22, 1.03it/s]\n 21%|██▏ | 6/28 [00:05<00:21, 1.02it/s]\n 25%|██▌ | 7/28 [00:06<00:20, 1.01it/s]\n 29%|██▊ | 8/28 [00:07<00:19, 1.01it/s]\n 32%|███▏ | 9/28 [00:08<00:18, 1.00it/s]\n 36%|███▌ | 10/28 [00:09<00:18, 1.00s/it]\n 39%|███▉ | 11/28 [00:10<00:17, 1.00s/it]\n 43%|████▎ | 12/28 [00:11<00:16, 1.00s/it]\n 46%|████▋ | 13/28 [00:12<00:15, 1.00s/it]\n 50%|█████ | 14/28 [00:13<00:14, 1.00s/it]\n 54%|█████▎ | 15/28 [00:14<00:13, 1.00s/it]\n 57%|█████▋ | 16/28 [00:15<00:12, 1.00s/it]\n 61%|██████ | 17/28 [00:16<00:11, 1.00s/it]\n 64%|██████▍ | 18/28 [00:17<00:10, 1.00s/it]\n 68%|██████▊ | 19/28 [00:18<00:09, 1.01s/it]\n 71%|███████▏ | 20/28 [00:19<00:08, 1.00s/it]\n 75%|███████▌ | 21/28 [00:20<00:07, 1.00s/it]\n 79%|███████▊ | 22/28 [00:21<00:06, 1.00s/it]\n 82%|████████▏ | 23/28 [00:22<00:05, 1.00s/it]\n 86%|████████▌ | 24/28 [00:23<00:04, 1.00s/it]\n 89%|████████▉ | 25/28 [00:24<00:03, 1.00s/it]\n 93%|█████████▎| 26/28 [00:25<00:02, 1.00s/it]\n 96%|█████████▋| 27/28 [00:26<00:01, 1.01s/it]\n100%|██████████| 28/28 [00:27<00:00, 1.01s/it]\n100%|██████████| 28/28 [00:27<00:00, 1.00it/s]",
"metrics": {
"predict_time": 42.463147175,
"total_time": 42.471559
},
"output": [
"https://replicate.delivery/yhqm/BraLreaMEHz0Iq9yqR4KquScGoIynNmrZx2Zq4qfUg9gIcXTA/out-0.png",
"https://replicate.delivery/yhqm/zMH89McQJDbvNBt7Kae0qgrgS9mYXtudzJQN9VOxIVGQEurJA/out-1.png",
"https://replicate.delivery/yhqm/gU7J5OxAQWKzDt4Q95Fg1UdJGfmpeZw7iMFRze7emi1BiwdNB/out-2.png",
"https://replicate.delivery/yhqm/u2V6V9fkuxXERqRqS1rgl6jlge5AidjYf7CPcSs3jd4BR4umA/out-3.png"
],
"started_at": "2024-08-29T06:06:46.223412Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/1wcbwktsrxrm40chkjz9722ga4",
"cancel": "https://api.replicate.com/v1/predictions/1wcbwktsrxrm40chkjz9722ga4/cancel"
},
"version": "cb1df38ccb4fd273f4a7731931372f567a11bf839cc95743aba67b15a668a5c7"
}
Using seed: 47241
Prompt: a photo of ckh a man with a beard, realistic photo taken in a vinyl record store
txt2img mode
Using dev model
free=9521626193920
Downloading weights
2024-08-29T06:06:46Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpb44_ivbj/weights url=https://replicate.delivery/yhqm/i4w5exJOYelkEEghRYXIXTxTEfAup2GFIC5jt48dWo9a5uumA/trained_model.tar
2024-08-29T06:06:48Z | INFO | [ Complete ] dest=/tmp/tmpb44_ivbj/weights size="172 MB" total_elapsed=2.530s url=https://replicate.delivery/yhqm/i4w5exJOYelkEEghRYXIXTxTEfAup2GFIC5jt48dWo9a5uumA/trained_model.tar
Downloaded weights in 2.56s
Loaded LoRAs in 11.42s
0%| | 0/28 [00:00<?, ?it/s]
4%|▎ | 1/28 [00:00<00:26, 1.00it/s]
7%|▋ | 2/28 [00:01<00:22, 1.15it/s]
11%|█ | 3/28 [00:02<00:23, 1.08it/s]
14%|█▍ | 4/28 [00:03<00:22, 1.04it/s]
18%|█▊ | 5/28 [00:04<00:22, 1.03it/s]
21%|██▏ | 6/28 [00:05<00:21, 1.02it/s]
25%|██▌ | 7/28 [00:06<00:20, 1.01it/s]
29%|██▊ | 8/28 [00:07<00:19, 1.01it/s]
32%|███▏ | 9/28 [00:08<00:18, 1.00it/s]
36%|███▌ | 10/28 [00:09<00:18, 1.00s/it]
39%|███▉ | 11/28 [00:10<00:17, 1.00s/it]
43%|████▎ | 12/28 [00:11<00:16, 1.00s/it]
46%|████▋ | 13/28 [00:12<00:15, 1.00s/it]
50%|█████ | 14/28 [00:13<00:14, 1.00s/it]
54%|█████▎ | 15/28 [00:14<00:13, 1.00s/it]
57%|█████▋ | 16/28 [00:15<00:12, 1.00s/it]
61%|██████ | 17/28 [00:16<00:11, 1.00s/it]
64%|██████▍ | 18/28 [00:17<00:10, 1.00s/it]
68%|██████▊ | 19/28 [00:18<00:09, 1.01s/it]
71%|███████▏ | 20/28 [00:19<00:08, 1.00s/it]
75%|███████▌ | 21/28 [00:20<00:07, 1.00s/it]
79%|███████▊ | 22/28 [00:21<00:06, 1.00s/it]
82%|████████▏ | 23/28 [00:22<00:05, 1.00s/it]
86%|████████▌ | 24/28 [00:23<00:04, 1.00s/it]
89%|████████▉ | 25/28 [00:24<00:03, 1.00s/it]
93%|█████████▎| 26/28 [00:25<00:02, 1.00s/it]
96%|█████████▋| 27/28 [00:26<00:01, 1.01s/it]
100%|██████████| 28/28 [00:27<00:00, 1.01s/it]
100%|██████████| 28/28 [00:27<00:00, 1.00it/s]
This model runs on Nvidia H100 GPU hardware. We don't yet have enough runs of this model to provide performance information.
This model doesn't have a readme.
This model is warm. You'll get a fast response if the model is warm and already running, and a slower response if the model is cold and starting up.
Choose a file from your machine
Hint: you can also drag files onto the input
Choose a file from your machine
Hint: you can also drag files onto the input
Using seed: 47241
Prompt: a photo of ckh a man with a beard, realistic photo taken in a vinyl record store
txt2img mode
Using dev model
free=9521626193920
Downloading weights
2024-08-29T06:06:46Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpb44_ivbj/weights url=https://replicate.delivery/yhqm/i4w5exJOYelkEEghRYXIXTxTEfAup2GFIC5jt48dWo9a5uumA/trained_model.tar
2024-08-29T06:06:48Z | INFO | [ Complete ] dest=/tmp/tmpb44_ivbj/weights size="172 MB" total_elapsed=2.530s url=https://replicate.delivery/yhqm/i4w5exJOYelkEEghRYXIXTxTEfAup2GFIC5jt48dWo9a5uumA/trained_model.tar
Downloaded weights in 2.56s
Loaded LoRAs in 11.42s
0%| | 0/28 [00:00<?, ?it/s]
4%|▎ | 1/28 [00:00<00:26, 1.00it/s]
7%|▋ | 2/28 [00:01<00:22, 1.15it/s]
11%|█ | 3/28 [00:02<00:23, 1.08it/s]
14%|█▍ | 4/28 [00:03<00:22, 1.04it/s]
18%|█▊ | 5/28 [00:04<00:22, 1.03it/s]
21%|██▏ | 6/28 [00:05<00:21, 1.02it/s]
25%|██▌ | 7/28 [00:06<00:20, 1.01it/s]
29%|██▊ | 8/28 [00:07<00:19, 1.01it/s]
32%|███▏ | 9/28 [00:08<00:18, 1.00it/s]
36%|███▌ | 10/28 [00:09<00:18, 1.00s/it]
39%|███▉ | 11/28 [00:10<00:17, 1.00s/it]
43%|████▎ | 12/28 [00:11<00:16, 1.00s/it]
46%|████▋ | 13/28 [00:12<00:15, 1.00s/it]
50%|█████ | 14/28 [00:13<00:14, 1.00s/it]
54%|█████▎ | 15/28 [00:14<00:13, 1.00s/it]
57%|█████▋ | 16/28 [00:15<00:12, 1.00s/it]
61%|██████ | 17/28 [00:16<00:11, 1.00s/it]
64%|██████▍ | 18/28 [00:17<00:10, 1.00s/it]
68%|██████▊ | 19/28 [00:18<00:09, 1.01s/it]
71%|███████▏ | 20/28 [00:19<00:08, 1.00s/it]
75%|███████▌ | 21/28 [00:20<00:07, 1.00s/it]
79%|███████▊ | 22/28 [00:21<00:06, 1.00s/it]
82%|████████▏ | 23/28 [00:22<00:05, 1.00s/it]
86%|████████▌ | 24/28 [00:23<00:04, 1.00s/it]
89%|████████▉ | 25/28 [00:24<00:03, 1.00s/it]
93%|█████████▎| 26/28 [00:25<00:02, 1.00s/it]
96%|█████████▋| 27/28 [00:26<00:01, 1.01s/it]
100%|██████████| 28/28 [00:27<00:00, 1.01s/it]
100%|██████████| 28/28 [00:27<00:00, 1.00it/s]