Prediction

Model

rainer1966-de/flux_rainer:7aa25b69

jc890c4349rm00chq0nb3wdc0m

Status

Succeeded

Source

Web

Hardware

H100

Total duration

89.5s

Created

over 1 year ago

Webhook

–

Input

prompt: photo of rainerLinkedIn on th emarket place of an histric old village, very laughing, big crowd, holding a newspaper "New Work Times" in his right hand, dark suit, a white shirt and a tie with the logo from the trained model rainerLinkedIn, holding a microphone, no ring at his fingers, all people in th ebackground are not be similar to rainerLinkedIn, realistic photo
aspect_ratio: 1:1
model: dev
num_outputs: 1
num_inference_steps: 28
guidance_scale: 3.5
output_format: webp
output_quality: 80
lora_scale: 1
extra_lora_scale: 0.8

{
  "aspect_ratio": "1:1",
  "extra_lora_scale": 0.8,
  "guidance_scale": 3.5,
  "lora_scale": 1,
  "model": "dev",
  "num_inference_steps": 28,
  "num_outputs": 1,
  "output_format": "webp",
  "output_quality": 80,
  "prompt": "photo of rainerLinkedIn on th emarket place of an histric old village, very laughing, big crowd, holding a newspaper \"New Work Times\" in his right hand, dark suit, a white shirt and a tie with the logo from the trained model rainerLinkedIn, holding a microphone, no ring at his fingers, all people in th ebackground are not be similar to rainerLinkedIn, realistic photo"
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_Pcm**********************************

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 rainer1966-de/flux_rainer using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "rainer1966-de/flux_rainer:7aa25b6979dc8a8dcbe0d47637eeeb5c22c89386ed5835e5cc068320c166a3b1",
  {
    input: {
      aspect_ratio: "1:1",
      extra_lora_scale: 0.8,
      guidance_scale: 3.5,
      lora_scale: 1,
      model: "dev",
      num_inference_steps: 28,
      num_outputs: 1,
      output_format: "webp",
      output_quality: 80,
      prompt: "photo of rainerLinkedIn on th emarket place of an histric old village, very laughing, big crowd, holding a newspaper \"New Work Times\" in his right hand, dark suit, a white shirt and a tie with the logo from the trained model rainerLinkedIn, holding a microphone, no ring at his fingers, all people in th ebackground are not be similar to rainerLinkedIn, realistic photo"
    }
  }
);

// 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.

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_Pcm**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

Run rainer1966-de/flux_rainer using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "rainer1966-de/flux_rainer:7aa25b6979dc8a8dcbe0d47637eeeb5c22c89386ed5835e5cc068320c166a3b1",
    input={
        "aspect_ratio": "1:1",
        "extra_lora_scale": 0.8,
        "guidance_scale": 3.5,
        "lora_scale": 1,
        "model": "dev",
        "num_inference_steps": 28,
        "num_outputs": 1,
        "output_format": "webp",
        "output_quality": 80,
        "prompt": "photo of rainerLinkedIn on th emarket place of an histric old village, very laughing, big crowd, holding a newspaper \"New Work Times\" in his right hand, dark suit, a white shirt and a tie with the logo from the trained model rainerLinkedIn, holding a microphone, no ring at his fingers, all people in th ebackground are not be similar to rainerLinkedIn, realistic photo"
    }
)

# To access the file URL:
print(output[0].url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output[0].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_Pcm**********************************

This is your API token. Keep it to yourself.

Run rainer1966-de/flux_rainer 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": "rainer1966-de/flux_rainer:7aa25b6979dc8a8dcbe0d47637eeeb5c22c89386ed5835e5cc068320c166a3b1",
    "input": {
      "aspect_ratio": "1:1",
      "extra_lora_scale": 0.8,
      "guidance_scale": 3.5,
      "lora_scale": 1,
      "model": "dev",
      "num_inference_steps": 28,
      "num_outputs": 1,
      "output_format": "webp",
      "output_quality": 80,
      "prompt": "photo of rainerLinkedIn on th emarket place of an histric old village, very laughing, big crowd, holding a newspaper \\"New Work Times\\" in his right hand, dark suit, a white shirt and a tie with the logo from the trained model rainerLinkedIn, holding a microphone, no ring at his fingers, all people in th ebackground are not be similar to rainerLinkedIn, realistic photo"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "id": "jc890c4349rm00chq0nb3wdc0m",
  "model": "rainer1966-de/flux_rainer",
  "version": "7aa25b6979dc8a8dcbe0d47637eeeb5c22c89386ed5835e5cc068320c166a3b1",
  "input": {
    "aspect_ratio": "1:1",
    "extra_lora_scale": 0.8,
    "guidance_scale": 3.5,
    "lora_scale": 1,
    "model": "dev",
    "num_inference_steps": 28,
    "num_outputs": 1,
    "output_format": "webp",
    "output_quality": 80,
    "prompt": "photo of rainerLinkedIn on th emarket place of an histric old village, very laughing, big crowd, holding a newspaper \"New Work Times\" in his right hand, dark suit, a white shirt and a tie with the logo from the trained model rainerLinkedIn, holding a microphone, no ring at his fingers, all people in th ebackground are not be similar to rainerLinkedIn, realistic photo"
  },
  "logs": "Using seed: 58928\nPrompt: photo of rainerLinkedIn on th emarket place of an histric old village, very laughing, big crowd, holding a newspaper \"New Work Times\" in his right hand, dark suit, a white shirt and a tie with the logo from the trained model rainerLinkedIn, holding a microphone, no ring at his fingers, all people in th ebackground are not be similar to rainerLinkedIn, realistic photo\ntxt2img mode\nUsing dev model\nLoaded LoRAs in 19.22s\nThe following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['be similar to rainerlinkedin, realistic photo']\n  0%|          | 0/28 [00:00<?, ?it/s]\n  4%|▎         | 1/28 [00:00<00:07,  3.63it/s]\n  7%|▋         | 2/28 [00:00<00:06,  4.19it/s]\n 11%|█         | 3/28 [00:00<00:06,  3.94it/s]\n 14%|█▍        | 4/28 [00:01<00:06,  3.83it/s]\n 18%|█▊        | 5/28 [00:01<00:06,  3.77it/s]\n 21%|██▏       | 6/28 [00:01<00:05,  3.73it/s]\n 25%|██▌       | 7/28 [00:01<00:05,  3.71it/s]\n 29%|██▊       | 8/28 [00:02<00:05,  3.70it/s]\n 32%|███▏      | 9/28 [00:02<00:05,  3.68it/s]\n 36%|███▌      | 10/28 [00:02<00:04,  3.68it/s]\n 39%|███▉      | 11/28 [00:02<00:04,  3.67it/s]\n 43%|████▎     | 12/28 [00:03<00:04,  3.67it/s]\n 46%|████▋     | 13/28 [00:03<00:04,  3.67it/s]\n 50%|█████     | 14/28 [00:03<00:03,  3.66it/s]\n 54%|█████▎    | 15/28 [00:04<00:03,  3.66it/s]\n 57%|█████▋    | 16/28 [00:04<00:03,  3.66it/s]\n 61%|██████    | 17/28 [00:04<00:03,  3.66it/s]\n 64%|██████▍   | 18/28 [00:04<00:02,  3.66it/s]\n 68%|██████▊   | 19/28 [00:05<00:02,  3.66it/s]\n 71%|███████▏  | 20/28 [00:05<00:02,  3.66it/s]\n 75%|███████▌  | 21/28 [00:05<00:01,  3.66it/s]\n 79%|███████▊  | 22/28 [00:05<00:01,  3.66it/s]\n 82%|████████▏ | 23/28 [00:06<00:01,  3.66it/s]\n 86%|████████▌ | 24/28 [00:06<00:01,  3.66it/s]\n 89%|████████▉ | 25/28 [00:06<00:00,  3.66it/s]\n 93%|█████████▎| 26/28 [00:07<00:00,  3.66it/s]\n 96%|█████████▋| 27/28 [00:07<00:00,  3.66it/s]\n100%|██████████| 28/28 [00:07<00:00,  3.66it/s]\n100%|██████████| 28/28 [00:07<00:00,  3.69it/s]",
  "output": [
    "https://replicate.delivery/yhqm/VBYqC2RcfVQQGKVRDmzhWxTYop9vfsIfmWpi4Y5ShAbw7YymA/out-0.webp"
  ],
  "data_removed": false,
  "error": null,
  "source": "web",
  "status": "succeeded",
  "created_at": "2024-09-03T13:54:39.522Z",
  "started_at": "2024-09-03T13:55:41.632703Z",
  "completed_at": "2024-09-03T13:56:08.997185Z",
  "urls": {
    "cancel": "https://api.replicate.com/v1/predictions/jc890c4349rm00chq0nb3wdc0m/cancel",
    "get": "https://api.replicate.com/v1/predictions/jc890c4349rm00chq0nb3wdc0m",
    "web": "https://replicate.com/p/jc890c4349rm00chq0nb3wdc0m"
  },
  "metrics": {
    "predict_time": 27.364481684,
    "total_time": 89.475185
  }
}

Generated in

27.4 seconds

Tweak it Report

Using seed: 58928 Prompt: photo of rainerLinkedIn on th emarket place of an histric old village, very laughing, big crowd, holding a newspaper "New Work Times" in his right hand, dark suit, a white shirt and a tie with the logo from the trained model rainerLinkedIn, holding a microphone, no ring at his fingers, all people in th ebackground are not be similar to rainerLinkedIn, realistic photo txt2img mode Using dev model Loaded LoRAs in 19.22s The following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['be similar to rainerlinkedin, realistic photo'] 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.63it/s] 7%|▋ | 2/28 [00:00<00:06, 4.19it/s] 11%|█ | 3/28 [00:00<00:06, 3.94it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.83it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.77it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.73it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.71it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.70it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.68it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.68it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.67it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.67it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.67it/s] 50%|█████ | 14/28 [00:03<00:03, 3.66it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.66it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.66it/s] 61%|██████ | 17/28 [00:04<00:03, 3.66it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.66it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.66it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.66it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.66it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.66it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.66it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.66it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.66it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.66it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.66it/s] 100%|██████████| 28/28 [00:07<00:00, 3.66it/s] 100%|██████████| 28/28 [00:07<00:00, 3.69it/s]