Prediction

dcamsdev/klm-lora-flux:b44d8509a34daf2f6bb469c31bb3e4864fc2660dddd496a994f65da395c8f8e6

Model

dcamsdev/klm-lora-flux:b44d8509

1at83vy6e1rm20chrcead7qxnr

Status

Succeeded

Source

Web

Hardware

H100

Total duration

18.2s

Created

8 months ago

Input

model: dev
prompt: A female KLM flight attendant windsurfing in the sea, looking at camera and smiling, colorful setting, in style of a film scene, cinematinc lighting, koda, film style
lora_scale: 0.94
num_outputs: 1
aspect_ratio: 1:1
output_format: webp
guidance_scale: 5.77
output_quality: 90
prompt_strength: 0.85
extra_lora_scale: 1
num_inference_steps: 28

{
  "model": "dev",
  "prompt": "A female KLM flight attendant windsurfing in the sea, looking at camera and smiling, colorful setting, in style of a film scene, cinematinc lighting, koda, film style",
  "lora_scale": 0.94,
  "num_outputs": 1,
  "aspect_ratio": "1:1",
  "output_format": "webp",
  "guidance_scale": 5.77,
  "output_quality": 90,
  "prompt_strength": 0.85,
  "extra_lora_scale": 1,
  "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 dcamsdev/klm-lora-flux using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "dcamsdev/klm-lora-flux:b44d8509a34daf2f6bb469c31bb3e4864fc2660dddd496a994f65da395c8f8e6",
  {
    input: {
      model: "dev",
      prompt: "A female KLM flight attendant windsurfing in the sea, looking at camera and smiling, colorful setting, in style of a film scene, cinematinc lighting, koda, film style",
      lora_scale: 0.94,
      num_outputs: 1,
      aspect_ratio: "1:1",
      output_format: "webp",
      guidance_scale: 5.77,
      output_quality: 90,
      prompt_strength: 0.85,
      extra_lora_scale: 1,
      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 dcamsdev/klm-lora-flux using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "dcamsdev/klm-lora-flux:b44d8509a34daf2f6bb469c31bb3e4864fc2660dddd496a994f65da395c8f8e6",
    input={
        "model": "dev",
        "prompt": "A female KLM flight attendant windsurfing in the sea, looking at camera and smiling, colorful setting, in style of a film scene, cinematinc lighting, koda, film style",
        "lora_scale": 0.94,
        "num_outputs": 1,
        "aspect_ratio": "1:1",
        "output_format": "webp",
        "guidance_scale": 5.77,
        "output_quality": 90,
        "prompt_strength": 0.85,
        "extra_lora_scale": 1,
        "num_inference_steps": 28
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Run dcamsdev/klm-lora-flux 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": "b44d8509a34daf2f6bb469c31bb3e4864fc2660dddd496a994f65da395c8f8e6",
    "input": {
      "model": "dev",
      "prompt": "A female KLM flight attendant windsurfing in the sea, looking at camera and smiling, colorful setting, in style of a film scene, cinematinc lighting, koda, film style",
      "lora_scale": 0.94,
      "num_outputs": 1,
      "aspect_ratio": "1:1",
      "output_format": "webp",
      "guidance_scale": 5.77,
      "output_quality": 90,
      "prompt_strength": 0.85,
      "extra_lora_scale": 1,
      "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": "2024-09-05T16:55:46.789645Z",
  "created_at": "2024-09-05T16:55:28.624000Z",
  "data_removed": false,
  "error": null,
  "id": "1at83vy6e1rm20chrcead7qxnr",
  "input": {
    "model": "dev",
    "prompt": "A female KLM flight attendant windsurfing in the sea, looking at camera and smiling, colorful setting, in style of a film scene, cinematinc lighting, koda, film style",
    "lora_scale": 0.94,
    "num_outputs": 1,
    "aspect_ratio": "1:1",
    "output_format": "webp",
    "guidance_scale": 5.77,
    "output_quality": 90,
    "prompt_strength": 0.85,
    "extra_lora_scale": 1,
    "num_inference_steps": 28
  },
  "logs": "Using seed: 37009\nPrompt: A female KLM flight attendant windsurfing in the sea, looking at camera and smiling, colorful setting, in style of a film scene, cinematinc lighting, koda, film style\n[!] txt2img mode\nUsing dev model\nfree=8459560759296\nDownloading weights\n2024-09-05T16:55:28Z | INFO  | [ Initiating ] chunk_size=150M dest=/tmp/tmp1muvasxo/weights url=https://replicate.delivery/yhqm/p0FaD61vYVpmCtW4RqCbce1Dk7avKxfNLW6Sx8QwTKrRi3ZTA/trained_model.tar\n2024-09-05T16:55:30Z | INFO  | [ Complete ] dest=/tmp/tmp1muvasxo/weights size=\"172 MB\" total_elapsed=1.373s url=https://replicate.delivery/yhqm/p0FaD61vYVpmCtW4RqCbce1Dk7avKxfNLW6Sx8QwTKrRi3ZTA/trained_model.tar\nDownloaded weights in 1.40s\nLoaded LoRAs in 9.62s\n  0%|          | 0/28 [00:00<?, ?it/s]\n  4%|▎         | 1/28 [00:00<00:07,  3.40it/s]\n  7%|▋         | 2/28 [00:00<00:06,  3.78it/s]\n 11%|█         | 3/28 [00:00<00:06,  3.64it/s]\n 14%|█▍        | 4/28 [00:01<00:06,  3.58it/s]\n 18%|█▊        | 5/28 [00:01<00:06,  3.56it/s]\n 21%|██▏       | 6/28 [00:01<00:06,  3.53it/s]\n 25%|██▌       | 7/28 [00:01<00:05,  3.52it/s]\n 29%|██▊       | 8/28 [00:02<00:05,  3.52it/s]\n 32%|███▏      | 9/28 [00:02<00:05,  3.50it/s]\n 36%|███▌      | 10/28 [00:02<00:05,  3.50it/s]\n 39%|███▉      | 11/28 [00:03<00:04,  3.50it/s]\n 43%|████▎     | 12/28 [00:03<00:04,  3.49it/s]\n 46%|████▋     | 13/28 [00:03<00:04,  3.49it/s]\n 50%|█████     | 14/28 [00:03<00:04,  3.49it/s]\n 54%|█████▎    | 15/28 [00:04<00:03,  3.48it/s]\n 57%|█████▋    | 16/28 [00:04<00:03,  3.49it/s]\n 61%|██████    | 17/28 [00:04<00:03,  3.49it/s]\n 64%|██████▍   | 18/28 [00:05<00:02,  3.49it/s]\n 68%|██████▊   | 19/28 [00:05<00:02,  3.49it/s]\n 71%|███████▏  | 20/28 [00:05<00:02,  3.49it/s]\n 75%|███████▌  | 21/28 [00:05<00:02,  3.49it/s]\n 79%|███████▊  | 22/28 [00:06<00:01,  3.48it/s]\n 82%|████████▏ | 23/28 [00:06<00:01,  3.49it/s]\n 86%|████████▌ | 24/28 [00:06<00:01,  3.48it/s]\n 89%|████████▉ | 25/28 [00:07<00:00,  3.49it/s]\n 93%|█████████▎| 26/28 [00:07<00:00,  3.49it/s]\n 96%|█████████▋| 27/28 [00:07<00:00,  3.48it/s]\n100%|██████████| 28/28 [00:07<00:00,  3.49it/s]\n100%|██████████| 28/28 [00:07<00:00,  3.50it/s]",
  "metrics": {
    "predict_time": 18.155520949,
    "total_time": 18.165645
  },
  "output": [
    "https://replicate.delivery/yhqm/PFK6S8rOuAKMB91CXlvKMZ8zI3lAtCZtdKFAiR8651pkUesJA/out-0.webp"
  ],
  "started_at": "2024-09-05T16:55:28.634124Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/1at83vy6e1rm20chrcead7qxnr",
    "cancel": "https://api.replicate.com/v1/predictions/1at83vy6e1rm20chrcead7qxnr/cancel"
  },
  "version": "b44d8509a34daf2f6bb469c31bb3e4864fc2660dddd496a994f65da395c8f8e6"
}

Generated in

18.2 seconds

Tweak it ShareReport

Using seed: 37009
Prompt: A female KLM flight attendant windsurfing in the sea, looking at camera and smiling, colorful setting, in style of a film scene, cinematinc lighting, koda, film style
[!] txt2img mode
Using dev model
free=8459560759296
Downloading weights
2024-09-05T16:55:28Z | INFO  | [ Initiating ] chunk_size=150M dest=/tmp/tmp1muvasxo/weights url=https://replicate.delivery/yhqm/p0FaD61vYVpmCtW4RqCbce1Dk7avKxfNLW6Sx8QwTKrRi3ZTA/trained_model.tar
2024-09-05T16:55:30Z | INFO  | [ Complete ] dest=/tmp/tmp1muvasxo/weights size="172 MB" total_elapsed=1.373s url=https://replicate.delivery/yhqm/p0FaD61vYVpmCtW4RqCbce1Dk7avKxfNLW6Sx8QwTKrRi3ZTA/trained_model.tar
Downloaded weights in 1.40s
Loaded LoRAs in 9.62s
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