Prediction
chenxwh/nova-t2i:9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3ID
xn4r2sdce5rm80cm10491r5nt4
Status
Succeeded
Source
Web
Hardware
L40S
Total duration
Created
Input
- prompt
- a shiba inu wearing a beret and black turtleneck.
- guidance_scale
- 5
- negative_prompt
- low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand
- num_diffusion_steps
- 25
- num_inference_steps
- 64
{
"prompt": "a shiba inu wearing a beret and black turtleneck.",
"guidance_scale": 5,
"negative_prompt": "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand",
"num_diffusion_steps": 25,
"num_inference_steps": 64
}Install Replicate’s Node.js client library:
npm install replicateSet the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:
import Replicate from "replicate";
import fs from "node:fs";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});Run chenxwh/nova-t2i using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"chenxwh/nova-t2i:9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3",
{
input: {
prompt: "a shiba inu wearing a beret and black turtleneck.",
guidance_scale: 5,
negative_prompt: "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand",
num_diffusion_steps: 25,
num_inference_steps: 64
}
}
);
// To access the file URL:
console.log(output.url()); //=> "http://example.com"
// To write the file to disk:
fs.writeFile("my-image.png", output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:
pip install replicateSet the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:
import replicateRun chenxwh/nova-t2i using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"chenxwh/nova-t2i:9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3",
input={
"prompt": "a shiba inu wearing a beret and black turtleneck.",
"guidance_scale": 5,
"negative_prompt": "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand",
"num_diffusion_steps": 25,
"num_inference_steps": 64
}
)
# To access the file URL:
print(output.url())
#=> "http://example.com"
# To write the file to disk:
with open("my-image.png", "wb") as file:
file.write(output.read())To learn more, take a look at the guide on getting started with Python.
Set the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run chenxwh/nova-t2i 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": "chenxwh/nova-t2i:9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3",
"input": {
"prompt": "a shiba inu wearing a beret and black turtleneck.",
"guidance_scale": 5,
"negative_prompt": "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand",
"num_diffusion_steps": 25,
"num_inference_steps": 64
}
}' \
https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{
"completed_at": "2024-12-27T12:14:08.344308Z",
"created_at": "2024-12-27T12:12:53.745000Z",
"data_removed": false,
"error": null,
"id": "xn4r2sdce5rm80cm10491r5nt4",
"input": {
"prompt": "a shiba inu wearing a beret and black turtleneck.",
"guidance_scale": 5,
"negative_prompt": "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand",
"num_diffusion_steps": 25,
"num_inference_steps": 64
},
"logs": "Using seed: 20663\n 0%| | 0/64 [00:00<?, ?it/s]\n 2%|▏ | 1/64 [00:00<00:10, 5.97it/s]\n 3%|▎ | 2/64 [00:00<00:08, 7.05it/s]\n 5%|▍ | 3/64 [00:00<00:08, 7.43it/s]\n 6%|▋ | 4/64 [00:00<00:07, 7.52it/s]\n 8%|▊ | 5/64 [00:00<00:07, 7.64it/s]\n 9%|▉ | 6/64 [00:00<00:07, 7.71it/s]\n 11%|█ | 7/64 [00:00<00:07, 7.73it/s]\n 12%|█▎ | 8/64 [00:01<00:07, 7.80it/s]\n 14%|█▍ | 9/64 [00:01<00:07, 7.77it/s]\n 16%|█▌ | 10/64 [00:01<00:06, 7.78it/s]\n 17%|█▋ | 11/64 [00:01<00:06, 7.79it/s]\n 19%|█▉ | 12/64 [00:01<00:06, 7.80it/s]\n 20%|██ | 13/64 [00:01<00:06, 7.81it/s]\n 22%|██▏ | 14/64 [00:01<00:06, 7.80it/s]\n 23%|██▎ | 15/64 [00:01<00:06, 7.79it/s]\n 25%|██▌ | 16/64 [00:02<00:06, 7.79it/s]\n 27%|██▋ | 17/64 [00:02<00:06, 7.78it/s]\n 28%|██▊ | 18/64 [00:02<00:05, 7.78it/s]\n 30%|██▉ | 19/64 [00:02<00:05, 7.75it/s]\n 31%|███▏ | 20/64 [00:02<00:05, 7.74it/s]\n 33%|███▎ | 21/64 [00:02<00:05, 7.61it/s]\n 34%|███▍ | 22/64 [00:02<00:05, 7.50it/s]\n 36%|███▌ | 23/64 [00:03<00:05, 7.43it/s]\n 38%|███▊ | 24/64 [00:03<00:05, 7.35it/s]\n 39%|███▉ | 25/64 [00:03<00:05, 7.05it/s]\n 41%|████ | 26/64 [00:03<00:05, 7.12it/s]\n 42%|████▏ | 27/64 [00:03<00:05, 7.15it/s]\n 44%|████▍ | 28/64 [00:03<00:05, 7.14it/s]\n 45%|████▌ | 29/64 [00:03<00:04, 7.05it/s]\n 47%|████▋ | 30/64 [00:04<00:04, 6.92it/s]\n 48%|████▊ | 31/64 [00:04<00:04, 6.94it/s]\n 50%|█████ | 32/64 [00:04<00:04, 6.90it/s]\n 52%|█████▏ | 33/64 [00:04<00:04, 6.86it/s]\n 53%|█████▎ | 34/64 [00:04<00:04, 6.65it/s]\n 55%|█████▍ | 35/64 [00:04<00:04, 6.69it/s]\n 56%|█████▋ | 36/64 [00:04<00:04, 6.74it/s]\n 58%|█████▊ | 37/64 [00:05<00:04, 6.73it/s]\n 59%|█████▉ | 38/64 [00:05<00:03, 6.70it/s]\n 61%|██████ | 39/64 [00:05<00:03, 6.66it/s]\n 62%|██████▎ | 40/64 [00:05<00:03, 6.46it/s]\n 64%|██████▍ | 41/64 [00:05<00:03, 6.50it/s]\n 66%|██████▌ | 42/64 [00:05<00:03, 6.51it/s]\n 67%|██████▋ | 43/64 [00:06<00:03, 6.36it/s]\n 69%|██████▉ | 44/64 [00:06<00:03, 6.28it/s]\n 70%|███████ | 45/64 [00:06<00:03, 6.20it/s]\n 72%|███████▏ | 46/64 [00:06<00:02, 6.19it/s]\n 73%|███████▎ | 47/64 [00:06<00:02, 6.14it/s]\n 75%|███████▌ | 48/64 [00:06<00:02, 6.05it/s]\n 77%|███████▋ | 49/64 [00:07<00:02, 5.94it/s]\n 78%|███████▊ | 50/64 [00:07<00:02, 5.90it/s]\n 80%|███████▉ | 51/64 [00:07<00:02, 5.84it/s]\n 81%|████████▏ | 52/64 [00:07<00:02, 5.81it/s]\n 83%|████████▎ | 53/64 [00:07<00:01, 5.77it/s]\n 84%|████████▍ | 54/64 [00:07<00:01, 5.76it/s]\n 86%|████████▌ | 55/64 [00:08<00:01, 5.70it/s]\n 88%|████████▊ | 56/64 [00:08<00:01, 5.61it/s]\n 89%|████████▉ | 57/64 [00:08<00:01, 5.55it/s]\n 91%|█████████ | 58/64 [00:08<00:01, 5.54it/s]\n 92%|█████████▏| 59/64 [00:08<00:00, 5.49it/s]\n 94%|█████████▍| 60/64 [00:08<00:00, 5.34it/s]\n 95%|█████████▌| 61/64 [00:09<00:00, 5.26it/s]\n 97%|█████████▋| 62/64 [00:09<00:00, 5.22it/s]\n 98%|█████████▊| 63/64 [00:09<00:00, 5.15it/s]\n100%|██████████| 64/64 [00:09<00:00, 5.03it/s]\n100%|██████████| 64/64 [00:09<00:00, 6.53it/s]",
"metrics": {
"predict_time": 10.546732175,
"total_time": 74.599308
},
"output": "https://replicate.delivery/xezq/TefYpvHO8mkQcEFQQY81mzLjS3kUbdAOo8NLR8Znf06ggJePB/out.png",
"started_at": "2024-12-27T12:13:57.797576Z",
"status": "succeeded",
"urls": {
"stream": "https://stream.replicate.com/v1/files/bcwr-3phkv55ne24qhxrvzt3oiwkt4a3vng5e7uvbyrtz4pzdekzt4axq",
"get": "https://api.replicate.com/v1/predictions/xn4r2sdce5rm80cm10491r5nt4",
"cancel": "https://api.replicate.com/v1/predictions/xn4r2sdce5rm80cm10491r5nt4/cancel"
},
"version": "9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3"
}Generated in
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