Prediction

esgfit/flux_andreas:cfbc437c2570f0f041e343cf1f695539a1ef7c693268a4cf8297960a58ad199d

Model

esgfit/flux_andreas:cfbc437c

d2xvessrmxrm60chq1t9shw5jg

Status

Succeeded

Source

Web

Hardware

H100

Total duration

64.9s

Created

8 months ago

Input

model: dev
prompt: Foto of AndreasLINKEDIN in front of a waterfall with hiking clothes in an athlethic pose
lora_scale: 1
num_outputs: 1
aspect_ratio: 1:1
output_format: webp
guidance_scale: 3.5
output_quality: 80
extra_lora_scale: 0.8
num_inference_steps: 28

{
  "model": "dev",
  "prompt": "Foto of AndreasLINKEDIN in front of a waterfall with hiking clothes in an athlethic pose",
  "lora_scale": 1,
  "num_outputs": 1,
  "aspect_ratio": "1:1",
  "output_format": "webp",
  "guidance_scale": 3.5,
  "output_quality": 80,
  "extra_lora_scale": 0.8,
  "num_inference_steps": 28
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

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

const output = await replicate.run(
  "esgfit/flux_andreas:cfbc437c2570f0f041e343cf1f695539a1ef7c693268a4cf8297960a58ad199d",
  {
    input: {
      model: "dev",
      prompt: "Foto of AndreasLINKEDIN in front of a waterfall with hiking clothes in an athlethic pose",
      lora_scale: 1,
      num_outputs: 1,
      aspect_ratio: "1:1",
      output_format: "webp",
      guidance_scale: 3.5,
      output_quality: 80,
      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.

Install Replicate’s Python client library:

pip install replicate

Import the client:

import replicate

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

output = replicate.run(
    "esgfit/flux_andreas:cfbc437c2570f0f041e343cf1f695539a1ef7c693268a4cf8297960a58ad199d",
    input={
        "model": "dev",
        "prompt": "Foto of AndreasLINKEDIN in front of a waterfall with hiking clothes in an athlethic pose",
        "lora_scale": 1,
        "num_outputs": 1,
        "aspect_ratio": "1:1",
        "output_format": "webp",
        "guidance_scale": 3.5,
        "output_quality": 80,
        "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.

Run esgfit/flux_andreas 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": "cfbc437c2570f0f041e343cf1f695539a1ef7c693268a4cf8297960a58ad199d",
    "input": {
      "model": "dev",
      "prompt": "Foto of AndreasLINKEDIN in front of a waterfall with hiking clothes in an athlethic pose",
      "lora_scale": 1,
      "num_outputs": 1,
      "aspect_ratio": "1:1",
      "output_format": "webp",
      "guidance_scale": 3.5,
      "output_quality": 80,
      "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.

Output

{
  "completed_at": "2024-09-03T15:16:14.984538Z",
  "created_at": "2024-09-03T15:15:10.119000Z",
  "data_removed": false,
  "error": null,
  "id": "d2xvessrmxrm60chq1t9shw5jg",
  "input": {
    "model": "dev",
    "prompt": "Foto of AndreasLINKEDIN in front of a waterfall with hiking clothes in an athlethic pose",
    "lora_scale": 1,
    "num_outputs": 1,
    "aspect_ratio": "1:1",
    "output_format": "webp",
    "guidance_scale": 3.5,
    "output_quality": 80,
    "extra_lora_scale": 0.8,
    "num_inference_steps": 28
  },
  "logs": "Using seed: 36028\nPrompt: Foto of AndreasLINKEDIN in front of a waterfall with hiking clothes in an athlethic pose\ntxt2img mode\nUsing dev model\nfree=9428070293504\nDownloading weights\n2024-09-03T15:15:57Z | INFO  | [ Initiating ] chunk_size=150M dest=/tmp/tmpszsd8hrq/weights url=https://replicate.delivery/yhqm/alihqHSlkPYRBlCskyyZrFgABmFuu4BiPeQFdTPjRX9DMlsJA/trained_model.tar\n2024-09-03T15:15:59Z | INFO  | [ Complete ] dest=/tmp/tmpszsd8hrq/weights size=\"172 MB\" total_elapsed=1.914s url=https://replicate.delivery/yhqm/alihqHSlkPYRBlCskyyZrFgABmFuu4BiPeQFdTPjRX9DMlsJA/trained_model.tar\nDownloaded weights in 1.94s\nLoaded LoRAs in 9.32s\n  0%|          | 0/28 [00:00<?, ?it/s]\n  4%|▎         | 1/28 [00:00<00:07,  3.65it/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,  3.76it/s]\n 21%|██▏       | 6/28 [00:01<00:05,  3.71it/s]\n 25%|██▌       | 7/28 [00:01<00:05,  3.70it/s]\n 29%|██▊       | 8/28 [00:02<00:05,  3.69it/s]\n 32%|███▏      | 9/28 [00:02<00:05,  3.67it/s]\n 36%|███▌      | 10/28 [00:02<00:04,  3.65it/s]\n 39%|███▉      | 11/28 [00:02<00:04,  3.65it/s]\n 43%|████▎     | 12/28 [00:03<00:04,  3.65it/s]\n 46%|████▋     | 13/28 [00:03<00:04,  3.64it/s]\n 50%|█████     | 14/28 [00:03<00:03,  3.64it/s]\n 54%|█████▎    | 15/28 [00:04<00:03,  3.65it/s]\n 57%|█████▋    | 16/28 [00:04<00:03,  3.65it/s]\n 61%|██████    | 17/28 [00:04<00:03,  3.64it/s]\n 64%|██████▍   | 18/28 [00:04<00:02,  3.64it/s]\n 68%|██████▊   | 19/28 [00:05<00:02,  3.65it/s]\n 71%|███████▏  | 20/28 [00:05<00:02,  3.65it/s]\n 75%|███████▌  | 21/28 [00:05<00:01,  3.64it/s]\n 79%|███████▊  | 22/28 [00:05<00:01,  3.64it/s]\n 82%|████████▏ | 23/28 [00:06<00:01,  3.65it/s]\n 86%|████████▌ | 24/28 [00:06<00:01,  3.65it/s]\n 89%|████████▉ | 25/28 [00:06<00:00,  3.64it/s]\n 93%|█████████▎| 26/28 [00:07<00:00,  3.64it/s]\n 96%|█████████▋| 27/28 [00:07<00:00,  3.64it/s]\n100%|██████████| 28/28 [00:07<00:00,  3.65it/s]\n100%|██████████| 28/28 [00:07<00:00,  3.67it/s]",
  "metrics": {
    "predict_time": 17.52221997,
    "total_time": 64.865538
  },
  "output": [
    "https://replicate.delivery/yhqm/sYctEfgeXigaV078xAxJezqhFeMhePG59UXMwuqJDo32HtJbC/out-0.webp"
  ],
  "started_at": "2024-09-03T15:15:57.462318Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/d2xvessrmxrm60chq1t9shw5jg",
    "cancel": "https://api.replicate.com/v1/predictions/d2xvessrmxrm60chq1t9shw5jg/cancel"
  },
  "version": "cfbc437c2570f0f041e343cf1f695539a1ef7c693268a4cf8297960a58ad199d"
}

Generated in

17.5 seconds

Tweak it ShareReport

Using seed: 36028
Prompt: Foto of AndreasLINKEDIN in front of a waterfall with hiking clothes in an athlethic pose
txt2img mode
Using dev model
free=9428070293504
Downloading weights
2024-09-03T15:15:57Z | INFO  | [ Initiating ] chunk_size=150M dest=/tmp/tmpszsd8hrq/weights url=https://replicate.delivery/yhqm/alihqHSlkPYRBlCskyyZrFgABmFuu4BiPeQFdTPjRX9DMlsJA/trained_model.tar
2024-09-03T15:15:59Z | INFO  | [ Complete ] dest=/tmp/tmpszsd8hrq/weights size="172 MB" total_elapsed=1.914s url=https://replicate.delivery/yhqm/alihqHSlkPYRBlCskyyZrFgABmFuu4BiPeQFdTPjRX9DMlsJA/trained_model.tar
Downloaded weights in 1.94s
Loaded LoRAs in 9.32s
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