Readme
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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 anjakuzev/gose_pub using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"anjakuzev/gose_pub:69d064dc24e7dacaa57dc1ff5547e84e54a587699599abacb3bcd0c6fad8bc3d",
{
input: {
width: 1024,
height: 1024,
prompt: "front shot, portrait of TOK with long hair, natural skin, daylight, (cinematic, film grain:1.1)",
refine: "no_refiner",
scheduler: "KarrasDPM",
lora_scale: 1,
num_outputs: 1,
guidance_scale: 7.5,
apply_watermark: false,
high_noise_frac: 0.95,
negative_prompt: "(deformed iris, deformed pupils, semi-realistic, cgi, 3d, render, sketch, cartoon, drawing, anime, mutated hands and fingers:1.4), (deformed, distorted, disfigured:1.3), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, disconnected limbs, mutation, mutated, ugly, disgusting, amputation, defromed EYES",
prompt_strength: 1,
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 anjakuzev/gose_pub using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"anjakuzev/gose_pub:69d064dc24e7dacaa57dc1ff5547e84e54a587699599abacb3bcd0c6fad8bc3d",
input={
"width": 1024,
"height": 1024,
"prompt": "front shot, portrait of TOK with long hair, natural skin, daylight, (cinematic, film grain:1.1)",
"refine": "no_refiner",
"scheduler": "KarrasDPM",
"lora_scale": 1,
"num_outputs": 1,
"guidance_scale": 7.5,
"apply_watermark": False,
"high_noise_frac": 0.95,
"negative_prompt": "(deformed iris, deformed pupils, semi-realistic, cgi, 3d, render, sketch, cartoon, drawing, anime, mutated hands and fingers:1.4), (deformed, distorted, disfigured:1.3), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, disconnected limbs, mutation, mutated, ugly, disgusting, amputation, defromed EYES",
"prompt_strength": 1,
"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 anjakuzev/gose_pub 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": "anjakuzev/gose_pub:69d064dc24e7dacaa57dc1ff5547e84e54a587699599abacb3bcd0c6fad8bc3d",
"input": {
"width": 1024,
"height": 1024,
"prompt": "front shot, portrait of TOK with long hair, natural skin, daylight, (cinematic, film grain:1.1)",
"refine": "no_refiner",
"scheduler": "KarrasDPM",
"lora_scale": 1,
"num_outputs": 1,
"guidance_scale": 7.5,
"apply_watermark": false,
"high_noise_frac": 0.95,
"negative_prompt": "(deformed iris, deformed pupils, semi-realistic, cgi, 3d, render, sketch, cartoon, drawing, anime, mutated hands and fingers:1.4), (deformed, distorted, disfigured:1.3), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, disconnected limbs, mutation, mutated, ugly, disgusting, amputation, defromed EYES",
"prompt_strength": 1,
"num_inference_steps": 50
}
}' \
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": "2023-12-18T16:15:58.483578Z",
"created_at": "2023-12-18T16:15:34.033853Z",
"data_removed": false,
"error": null,
"id": "hmvpywlbbvwvovsrwazcv6qpma",
"input": {
"width": 1024,
"height": 1024,
"prompt": "front shot, portrait of TOK with long hair, natural skin, daylight, (cinematic, film grain:1.1)",
"refine": "no_refiner",
"scheduler": "KarrasDPM",
"lora_scale": 1,
"num_outputs": 1,
"guidance_scale": 7.5,
"apply_watermark": false,
"high_noise_frac": 0.95,
"negative_prompt": "(deformed iris, deformed pupils, semi-realistic, cgi, 3d, render, sketch, cartoon, drawing, anime, mutated hands and fingers:1.4), (deformed, distorted, disfigured:1.3), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, disconnected limbs, mutation, mutated, ugly, disgusting, amputation, defromed EYES",
"prompt_strength": 1,
"num_inference_steps": 50
},
"logs": "Using seed: 33108\nEnsuring enough disk space...\nFree disk space: 2855291240448\nDownloading weights: https://replicate.delivery/pbxt/2Tu1bSIK86KlKN0yQ1GSzXx7aa6XTiXHK6meU5hBFyGA1wBJA/trained_model.tar\n2023-12-18T16:15:42Z | INFO | [ Initiating ] dest=/src/weights-cache/5c767c5c0e88a07c minimum_chunk_size=150M url=https://replicate.delivery/pbxt/2Tu1bSIK86KlKN0yQ1GSzXx7aa6XTiXHK6meU5hBFyGA1wBJA/trained_model.tar\n2023-12-18T16:15:43Z | INFO | [ Complete ] dest=/src/weights-cache/5c767c5c0e88a07c size=\"186 MB\" total_elapsed=0.989s url=https://replicate.delivery/pbxt/2Tu1bSIK86KlKN0yQ1GSzXx7aa6XTiXHK6meU5hBFyGA1wBJA/trained_model.tar\nb''\nDownloaded weights in 1.1449191570281982 seconds\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: front shot, portrait of <s0><s1> with long hair, natural skin, daylight, (cinematic, film grain:1.1)\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:13, 3.66it/s]\n 4%|▍ | 2/50 [00:00<00:13, 3.65it/s]\n 6%|▌ | 3/50 [00:00<00:12, 3.66it/s]\n 8%|▊ | 4/50 [00:01<00:12, 3.66it/s]\n 10%|█ | 5/50 [00:01<00:12, 3.66it/s]\n 12%|█▏ | 6/50 [00:01<00:12, 3.66it/s]\n 14%|█▍ | 7/50 [00:01<00:11, 3.66it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.66it/s]\n 18%|█▊ | 9/50 [00:02<00:11, 3.66it/s]\n 20%|██ | 10/50 [00:02<00:10, 3.66it/s]\n 22%|██▏ | 11/50 [00:03<00:10, 3.66it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.66it/s]\n 26%|██▌ | 13/50 [00:03<00:10, 3.66it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.66it/s]\n 30%|███ | 15/50 [00:04<00:09, 3.66it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.65it/s]\n 34%|███▍ | 17/50 [00:04<00:09, 3.65it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.65it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.65it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.65it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 3.65it/s]\n 44%|████▍ | 22/50 [00:06<00:07, 3.65it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.65it/s]\n 48%|████▊ | 24/50 [00:06<00:07, 3.65it/s]\n 50%|█████ | 25/50 [00:06<00:06, 3.65it/s]\n 52%|█████▏ | 26/50 [00:07<00:06, 3.64it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.64it/s]\n 56%|█████▌ | 28/50 [00:07<00:06, 3.64it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 3.64it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.64it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.64it/s]\n 64%|██████▍ | 32/50 [00:08<00:04, 3.64it/s]\n 66%|██████▌ | 33/50 [00:09<00:04, 3.64it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.64it/s]\n 70%|███████ | 35/50 [00:09<00:04, 3.64it/s]\n 72%|███████▏ | 36/50 [00:09<00:03, 3.64it/s]\n 74%|███████▍ | 37/50 [00:10<00:03, 3.64it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.64it/s]\n 78%|███████▊ | 39/50 [00:10<00:03, 3.64it/s]\n 80%|████████ | 40/50 [00:10<00:02, 3.64it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.63it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.64it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.64it/s]\n 88%|████████▊ | 44/50 [00:12<00:01, 3.64it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.64it/s]\n 92%|█████████▏| 46/50 [00:12<00:01, 3.64it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.64it/s]\n 96%|█████████▌| 48/50 [00:13<00:00, 3.63it/s]\n98%|█████████▊| 49/50 [00:13<00:00, 3.63it/s]\n98%|█████████▊| 49/50 [00:13<00:00, 3.65it/s]",
"metrics": {
"predict_time": 16.267976,
"total_time": 24.449725
},
"output": [
"https://replicate.delivery/pbxt/1uj1sr5I15KMFxa0qrTfRWr4kA47uFZxxVC5Xh3eAMmeREHkA/out-0.png"
],
"started_at": "2023-12-18T16:15:42.215602Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/hmvpywlbbvwvovsrwazcv6qpma",
"cancel": "https://api.replicate.com/v1/predictions/hmvpywlbbvwvovsrwazcv6qpma/cancel"
},
"version": "69d064dc24e7dacaa57dc1ff5547e84e54a587699599abacb3bcd0c6fad8bc3d"
}
Using seed: 33108
Ensuring enough disk space...
Free disk space: 2855291240448
Downloading weights: https://replicate.delivery/pbxt/2Tu1bSIK86KlKN0yQ1GSzXx7aa6XTiXHK6meU5hBFyGA1wBJA/trained_model.tar
2023-12-18T16:15:42Z | INFO | [ Initiating ] dest=/src/weights-cache/5c767c5c0e88a07c minimum_chunk_size=150M url=https://replicate.delivery/pbxt/2Tu1bSIK86KlKN0yQ1GSzXx7aa6XTiXHK6meU5hBFyGA1wBJA/trained_model.tar
2023-12-18T16:15:43Z | INFO | [ Complete ] dest=/src/weights-cache/5c767c5c0e88a07c size="186 MB" total_elapsed=0.989s url=https://replicate.delivery/pbxt/2Tu1bSIK86KlKN0yQ1GSzXx7aa6XTiXHK6meU5hBFyGA1wBJA/trained_model.tar
b''
Downloaded weights in 1.1449191570281982 seconds
Loading fine-tuned model
Does not have Unet. assume we are using LoRA
Loading Unet LoRA
Prompt: front shot, portrait of <s0><s1> with long hair, natural skin, daylight, (cinematic, film grain:1.1)
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This model costs approximately $0.022 to run on Replicate, or 45 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.
This model runs on Nvidia L40S GPU hardware. Predictions typically complete within 23 seconds.
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: 33108
Ensuring enough disk space...
Free disk space: 2855291240448
Downloading weights: https://replicate.delivery/pbxt/2Tu1bSIK86KlKN0yQ1GSzXx7aa6XTiXHK6meU5hBFyGA1wBJA/trained_model.tar
2023-12-18T16:15:42Z | INFO | [ Initiating ] dest=/src/weights-cache/5c767c5c0e88a07c minimum_chunk_size=150M url=https://replicate.delivery/pbxt/2Tu1bSIK86KlKN0yQ1GSzXx7aa6XTiXHK6meU5hBFyGA1wBJA/trained_model.tar
2023-12-18T16:15:43Z | INFO | [ Complete ] dest=/src/weights-cache/5c767c5c0e88a07c size="186 MB" total_elapsed=0.989s url=https://replicate.delivery/pbxt/2Tu1bSIK86KlKN0yQ1GSzXx7aa6XTiXHK6meU5hBFyGA1wBJA/trained_model.tar
b''
Downloaded weights in 1.1449191570281982 seconds
Loading fine-tuned model
Does not have Unet. assume we are using LoRA
Loading Unet LoRA
Prompt: front shot, portrait of <s0><s1> with long hair, natural skin, daylight, (cinematic, film grain:1.1)
txt2img mode
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