Prediction

Model

chenxwh/cogview3:9bb5091b

fymhagqpqxrgp0cjhmerev4pwc

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

4m 27s

Created

about 1 year ago

Webhook

–

Input

prompt: a photo of an astronaut riding a horse on mars
negative_prompt: Empty string
width: 1024
height: 1024
num_inference_steps: 50
guidance_scale: 7

{
  "guidance_scale": 7,
  "height": 1024,
  "negative_prompt": "",
  "num_inference_steps": 50,
  "prompt": "a photo of an astronaut riding a horse on mars",
  "width": 1024
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_Bix**********************************

This is your API token. Keep it to yourself.

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/cogview3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "chenxwh/cogview3:9bb5091b11777296d31136d6ba887ad2129044eb211b37b76479064f9bd78f9e",
  {
    input: {
      guidance_scale: 7,
      height: 1024,
      negative_prompt: "",
      num_inference_steps: 50,
      prompt: "a photo of an astronaut riding a horse on mars",
      width: 1024
    }
  }
);

// 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 replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_Bix**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

Run chenxwh/cogview3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "chenxwh/cogview3:9bb5091b11777296d31136d6ba887ad2129044eb211b37b76479064f9bd78f9e",
    input={
        "guidance_scale": 7,
        "height": 1024,
        "negative_prompt": "",
        "num_inference_steps": 50,
        "prompt": "a photo of an astronaut riding a horse on mars",
        "width": 1024
    }
)

# 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=r8_Bix**********************************

This is your API token. Keep it to yourself.

Run chenxwh/cogview3 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/cogview3:9bb5091b11777296d31136d6ba887ad2129044eb211b37b76479064f9bd78f9e",
    "input": {
      "guidance_scale": 7,
      "height": 1024,
      "negative_prompt": "",
      "num_inference_steps": 50,
      "prompt": "a photo of an astronaut riding a horse on mars",
      "width": 1024
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

{
  "id": "fymhagqpqxrgp0cjhmerev4pwc",
  "model": "chenxwh/cogview3",
  "version": "9bb5091b11777296d31136d6ba887ad2129044eb211b37b76479064f9bd78f9e",
  "input": {
    "guidance_scale": 7,
    "height": 1024,
    "negative_prompt": "",
    "num_inference_steps": 50,
    "prompt": "a photo of an astronaut riding a horse on mars",
    "width": 1024
  },
  "logs": "Using seed: 26279\n  0%|          | 0/50 [00:00<?, ?it/s]\n  2%|▏         | 1/50 [00:04<04:04,  4.99s/it]\n  4%|▍         | 2/50 [00:05<01:59,  2.48s/it]\n  6%|▌         | 3/50 [00:06<01:18,  1.68s/it]\n  8%|▊         | 4/50 [00:07<00:59,  1.30s/it]\n 10%|█         | 5/50 [00:07<00:49,  1.09s/it]\n 12%|█▏        | 6/50 [00:08<00:42,  1.03it/s]\n 14%|█▍        | 7/50 [00:09<00:38,  1.12it/s]\n 16%|█▌        | 8/50 [00:10<00:35,  1.20it/s]\n 18%|█▊        | 9/50 [00:10<00:32,  1.25it/s]\n 20%|██        | 10/50 [00:11<00:31,  1.29it/s]\n 22%|██▏       | 11/50 [00:12<00:29,  1.32it/s]\n 24%|██▍       | 12/50 [00:12<00:28,  1.34it/s]\n 26%|██▌       | 13/50 [00:13<00:27,  1.35it/s]\n 28%|██▊       | 14/50 [00:14<00:26,  1.36it/s]\n 30%|███       | 15/50 [00:15<00:25,  1.37it/s]\n 32%|███▏      | 16/50 [00:15<00:24,  1.37it/s]\n 34%|███▍      | 17/50 [00:16<00:23,  1.38it/s]\n 36%|███▌      | 18/50 [00:17<00:23,  1.38it/s]\n 38%|███▊      | 19/50 [00:18<00:22,  1.38it/s]\n 40%|████      | 20/50 [00:18<00:21,  1.38it/s]\n 42%|████▏     | 21/50 [00:19<00:21,  1.38it/s]\n 44%|████▍     | 22/50 [00:20<00:20,  1.38it/s]\n 46%|████▌     | 23/50 [00:20<00:19,  1.38it/s]\n 48%|████▊     | 24/50 [00:21<00:18,  1.38it/s]\n 50%|█████     | 25/50 [00:22<00:18,  1.38it/s]\n 52%|█████▏    | 26/50 [00:23<00:17,  1.38it/s]\n 54%|█████▍    | 27/50 [00:23<00:16,  1.38it/s]\n 56%|█████▌    | 28/50 [00:24<00:15,  1.38it/s]\n 58%|█████▊    | 29/50 [00:25<00:15,  1.38it/s]\n 60%|██████    | 30/50 [00:25<00:14,  1.37it/s]\n 62%|██████▏   | 31/50 [00:26<00:13,  1.37it/s]\n 64%|██████▍   | 32/50 [00:27<00:13,  1.37it/s]\n 66%|██████▌   | 33/50 [00:28<00:12,  1.37it/s]\n 68%|██████▊   | 34/50 [00:28<00:11,  1.37it/s]\n 70%|███████   | 35/50 [00:29<00:10,  1.37it/s]\n 72%|███████▏  | 36/50 [00:30<00:10,  1.37it/s]\n 74%|███████▍  | 37/50 [00:31<00:09,  1.37it/s]\n 76%|███████▌  | 38/50 [00:31<00:08,  1.37it/s]\n 78%|███████▊  | 39/50 [00:32<00:08,  1.37it/s]\n 80%|████████  | 40/50 [00:33<00:07,  1.37it/s]\n 82%|████████▏ | 41/50 [00:34<00:06,  1.37it/s]\n 84%|████████▍ | 42/50 [00:34<00:05,  1.37it/s]\n 86%|████████▌ | 43/50 [00:35<00:05,  1.37it/s]\n 88%|████████▊ | 44/50 [00:36<00:04,  1.37it/s]\n 90%|█████████ | 45/50 [00:36<00:03,  1.37it/s]\n 92%|█████████▏| 46/50 [00:37<00:02,  1.37it/s]\n 94%|█████████▍| 47/50 [00:38<00:02,  1.37it/s]\n 96%|█████████▌| 48/50 [00:39<00:01,  1.37it/s]\n 98%|█████████▊| 49/50 [00:39<00:00,  1.37it/s]\n100%|██████████| 50/50 [00:40<00:00,  1.37it/s]\n100%|██████████| 50/50 [00:40<00:00,  1.23it/s]",
  "output": "https://replicate.delivery/pbxt/XapoTdLQD2oHLlD2ILTsZCgrTbkRH8LI4rnjCovJqUrHMt5E/out.png",
  "data_removed": false,
  "error": null,
  "source": "web",
  "status": "succeeded",
  "created_at": "2024-10-14T22:20:04.159Z",
  "started_at": "2024-10-14T22:23:44.028416Z",
  "completed_at": "2024-10-14T22:24:31.42039Z",
  "urls": {
    "cancel": "https://api.replicate.com/v1/predictions/fymhagqpqxrgp0cjhmerev4pwc/cancel",
    "get": "https://api.replicate.com/v1/predictions/fymhagqpqxrgp0cjhmerev4pwc",
    "web": "https://replicate.com/p/fymhagqpqxrgp0cjhmerev4pwc"
  },
  "metrics": {
    "predict_time": 47.391973947,
    "total_time": 267.26139
  }
}

Generated in

47.4 seconds

Tweak it Report

Using seed: 26279 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:04<04:04, 4.99s/it] 4%|▍ | 2/50 [00:05<01:59, 2.48s/it] 6%|▌ | 3/50 [00:06<01:18, 1.68s/it] 8%|▊ | 4/50 [00:07<00:59, 1.30s/it] 10%|█ | 5/50 [00:07<00:49, 1.09s/it] 12%|█▏ | 6/50 [00:08<00:42, 1.03it/s] 14%|█▍ | 7/50 [00:09<00:38, 1.12it/s] 16%|█▌ | 8/50 [00:10<00:35, 1.20it/s] 18%|█▊ | 9/50 [00:10<00:32, 1.25it/s] 20%|██ | 10/50 [00:11<00:31, 1.29it/s] 22%|██▏ | 11/50 [00:12<00:29, 1.32it/s] 24%|██▍ | 12/50 [00:12<00:28, 1.34it/s] 26%|██▌ | 13/50 [00:13<00:27, 1.35it/s] 28%|██▊ | 14/50 [00:14<00:26, 1.36it/s] 30%|███ | 15/50 [00:15<00:25, 1.37it/s] 32%|███▏ | 16/50 [00:15<00:24, 1.37it/s] 34%|███▍ | 17/50 [00:16<00:23, 1.38it/s] 36%|███▌ | 18/50 [00:17<00:23, 1.38it/s] 38%|███▊ | 19/50 [00:18<00:22, 1.38it/s] 40%|████ | 20/50 [00:18<00:21, 1.38it/s] 42%|████▏ | 21/50 [00:19<00:21, 1.38it/s] 44%|████▍ | 22/50 [00:20<00:20, 1.38it/s] 46%|████▌ | 23/50 [00:20<00:19, 1.38it/s] 48%|████▊ | 24/50 [00:21<00:18, 1.38it/s] 50%|█████ | 25/50 [00:22<00:18, 1.38it/s] 52%|█████▏ | 26/50 [00:23<00:17, 1.38it/s] 54%|█████▍ | 27/50 [00:23<00:16, 1.38it/s] 56%|█████▌ | 28/50 [00:24<00:15, 1.38it/s] 58%|█████▊ | 29/50 [00:25<00:15, 1.38it/s] 60%|██████ | 30/50 [00:25<00:14, 1.37it/s] 62%|██████▏ | 31/50 [00:26<00:13, 1.37it/s] 64%|██████▍ | 32/50 [00:27<00:13, 1.37it/s] 66%|██████▌ | 33/50 [00:28<00:12, 1.37it/s] 68%|██████▊ | 34/50 [00:28<00:11, 1.37it/s] 70%|███████ | 35/50 [00:29<00:10, 1.37it/s] 72%|███████▏ | 36/50 [00:30<00:10, 1.37it/s] 74%|███████▍ | 37/50 [00:31<00:09, 1.37it/s] 76%|███████▌ | 38/50 [00:31<00:08, 1.37it/s] 78%|███████▊ | 39/50 [00:32<00:08, 1.37it/s] 80%|████████ | 40/50 [00:33<00:07, 1.37it/s] 82%|████████▏ | 41/50 [00:34<00:06, 1.37it/s] 84%|████████▍ | 42/50 [00:34<00:05, 1.37it/s] 86%|████████▌ | 43/50 [00:35<00:05, 1.37it/s] 88%|████████▊ | 44/50 [00:36<00:04, 1.37it/s] 90%|█████████ | 45/50 [00:36<00:03, 1.37it/s] 92%|█████████▏| 46/50 [00:37<00:02, 1.37it/s] 94%|█████████▍| 47/50 [00:38<00:02, 1.37it/s] 96%|█████████▌| 48/50 [00:39<00:01, 1.37it/s] 98%|█████████▊| 49/50 [00:39<00:00, 1.37it/s] 100%|██████████| 50/50 [00:40<00:00, 1.37it/s] 100%|██████████| 50/50 [00:40<00:00, 1.23it/s]