Prediction

Model

deepfates/flux-fallenchungus:810f7563

58bbmgc40drm80cm8yvvwwsv7w

Status

Succeeded

Source

Web

Hardware

H100

Total duration

7.7s

Created

11 months ago

Webhook

–

Input

prompt: CHNGS line drawing drawing of a gold mannequin head with a large wig made of colorful flowers and green leafy vines. the caption reads WELCOME TO THE DEEP FATES PROGRAM
aspect_ratio: 1:1
prompt_strength: 0.8
model: dev
num_outputs: 1
num_inference_steps: 50
guidance_scale: 4
seed: 40402
output_format: webp
output_quality: 80
go_fast: true
megapixels: 1
lora_scale: 1
extra_lora_scale: 1

{
  "aspect_ratio": "1:1",
  "extra_lora_scale": 1,
  "go_fast": true,
  "guidance_scale": 4,
  "lora_scale": 1,
  "megapixels": "1",
  "model": "dev",
  "num_inference_steps": 50,
  "num_outputs": 1,
  "output_format": "webp",
  "output_quality": 80,
  "prompt": " CHNGS line drawing drawing of a gold mannequin head with a large wig made of colorful flowers and green leafy vines. the caption reads WELCOME TO THE DEEP FATES PROGRAM",
  "prompt_strength": 0.8,
  "seed": 40402
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_TF1**********************************

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

const output = await replicate.run(
  "deepfates/flux-fallenchungus:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7",
  {
    input: {
      aspect_ratio: "1:1",
      extra_lora_scale: 1,
      go_fast: true,
      guidance_scale: 4,
      lora_scale: 1,
      megapixels: "1",
      model: "dev",
      num_inference_steps: 50,
      num_outputs: 1,
      output_format: "webp",
      output_quality: 80,
      prompt: " CHNGS line drawing drawing of a gold mannequin head with a large wig made of colorful flowers and green leafy vines. the caption reads WELCOME TO THE DEEP FATES PROGRAM",
      prompt_strength: 0.8,
      seed: 40402
    }
  }
);

// 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_TF1**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

Run deepfates/flux-fallenchungus using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "deepfates/flux-fallenchungus:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7",
    input={
        "aspect_ratio": "1:1",
        "extra_lora_scale": 1,
        "go_fast": True,
        "guidance_scale": 4,
        "lora_scale": 1,
        "megapixels": "1",
        "model": "dev",
        "num_inference_steps": 50,
        "num_outputs": 1,
        "output_format": "webp",
        "output_quality": 80,
        "prompt": " CHNGS line drawing drawing of a gold mannequin head with a large wig made of colorful flowers and green leafy vines. the caption reads WELCOME TO THE DEEP FATES PROGRAM",
        "prompt_strength": 0.8,
        "seed": 40402
    }
)

# 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_TF1**********************************

This is your API token. Keep it to yourself.

Run deepfates/flux-fallenchungus 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": "deepfates/flux-fallenchungus:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7",
    "input": {
      "aspect_ratio": "1:1",
      "extra_lora_scale": 1,
      "go_fast": true,
      "guidance_scale": 4,
      "lora_scale": 1,
      "megapixels": "1",
      "model": "dev",
      "num_inference_steps": 50,
      "num_outputs": 1,
      "output_format": "webp",
      "output_quality": 80,
      "prompt": " CHNGS line drawing drawing of a gold mannequin head with a large wig made of colorful flowers and green leafy vines. the caption reads WELCOME TO THE DEEP FATES PROGRAM",
      "prompt_strength": 0.8,
      "seed": 40402
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "id": "58bbmgc40drm80cm8yvvwwsv7w",
  "model": "deepfates/flux-fallenchungus",
  "version": "810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7",
  "input": {
    "aspect_ratio": "1:1",
    "extra_lora_scale": 1,
    "go_fast": true,
    "guidance_scale": 4,
    "lora_scale": 1,
    "megapixels": "1",
    "model": "dev",
    "num_inference_steps": 50,
    "num_outputs": 1,
    "output_format": "webp",
    "output_quality": 80,
    "prompt": " CHNGS line drawing drawing of a gold mannequin head with a large wig made of colorful flowers and green leafy vines. the caption reads WELCOME TO THE DEEP FATES PROGRAM",
    "prompt_strength": 0.8,
    "seed": 40402
  },
  "logs": "free=29090082111488\nDownloading weights\n2025-01-08T20:59:56Z | INFO  | [ Initiating ] chunk_size=150M dest=/tmp/tmpe_srp632/weights url=https://replicate.delivery/xezq/N4MICfLsnzyAKCROeM4SiQUWOCu0HxDrtWPVIejfDYEywlMQB/trained_model.tar\n2025-01-08T20:59:59Z | INFO  | [ Complete ] dest=/tmp/tmpe_srp632/weights size=\"172 MB\" total_elapsed=2.520s url=https://replicate.delivery/xezq/N4MICfLsnzyAKCROeM4SiQUWOCu0HxDrtWPVIejfDYEywlMQB/trained_model.tar\nDownloaded weights in 2.54s\n2025-01-08 20:59:59.439 | INFO     | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/245b1ac6b179a69f\n2025-01-08 20:59:59.509 | INFO     | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2025-01-08 20:59:59.510 | DEBUG    | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-08 20:59:59.510 | DEBUG    | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA:   0%|          | 0/304 [00:00<?, ?it/s]\nApplying LoRA:  41%|████▏     | 126/304 [00:00<00:00, 1237.22it/s]\nApplying LoRA:  82%|████████▏ | 250/304 [00:00<00:00, 948.25it/s] \nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 982.00it/s]\n2025-01-08 20:59:59.820 | SUCCESS  | fp8.lora_loading:load_lora:539 - LoRA applied in 0.38s\nrunning quantized prediction\nUsing seed: 40402\n  0%|          | 0/50 [00:00<?, ?it/s]\n  4%|▍         | 2/50 [00:00<00:02, 18.20it/s]\n  8%|▊         | 4/50 [00:00<00:03, 13.57it/s]\n 12%|█▏        | 6/50 [00:00<00:03, 12.53it/s]\n 16%|█▌        | 8/50 [00:00<00:03, 12.11it/s]\n 20%|██        | 10/50 [00:00<00:03, 11.85it/s]\n 24%|██▍       | 12/50 [00:00<00:03, 11.50it/s]\n 28%|██▊       | 14/50 [00:01<00:03, 11.45it/s]\n 32%|███▏      | 16/50 [00:01<00:02, 11.46it/s]\n 36%|███▌      | 18/50 [00:01<00:02, 11.47it/s]\n 40%|████      | 20/50 [00:01<00:02, 11.46it/s]\n 44%|████▍     | 22/50 [00:01<00:02, 11.39it/s]\n 48%|████▊     | 24/50 [00:02<00:02, 11.30it/s]\n 52%|█████▏    | 26/50 [00:02<00:02, 11.32it/s]\n 56%|█████▌    | 28/50 [00:02<00:01, 11.37it/s]\n 60%|██████    | 30/50 [00:02<00:01, 11.41it/s]\n 64%|██████▍   | 32/50 [00:02<00:01, 11.41it/s]\n 68%|██████▊   | 34/50 [00:02<00:01, 11.35it/s]\n 72%|███████▏  | 36/50 [00:03<00:01, 11.33it/s]\n 76%|███████▌  | 38/50 [00:03<00:01, 11.35it/s]\n 80%|████████  | 40/50 [00:03<00:00, 11.39it/s]\n 84%|████████▍ | 42/50 [00:03<00:00, 11.40it/s]\n 88%|████████▊ | 44/50 [00:03<00:00, 11.38it/s]\n 92%|█████████▏| 46/50 [00:03<00:00, 11.35it/s]\n 96%|█████████▌| 48/50 [00:04<00:00, 11.35it/s]\n100%|██████████| 50/50 [00:04<00:00, 11.35it/s]\n100%|██████████| 50/50 [00:04<00:00, 11.54it/s]\nTotal safe images: 1 out of 1",
  "output": [
    "https://replicate.delivery/xezq/PWArKmjTMZIBC9W29nzz87ZnIOTyXRHHVqG2qwOBrdMVZyAF/out-0.webp"
  ],
  "data_removed": false,
  "error": null,
  "source": "web",
  "status": "succeeded",
  "created_at": "2025-01-08T20:59:56.803Z",
  "started_at": "2025-01-08T20:59:56.894357Z",
  "completed_at": "2025-01-08T21:00:04.476377Z",
  "urls": {
    "cancel": "https://api.replicate.com/v1/predictions/58bbmgc40drm80cm8yvvwwsv7w/cancel",
    "get": "https://api.replicate.com/v1/predictions/58bbmgc40drm80cm8yvvwwsv7w",
    "stream": "https://stream.replicate.com/v1/files/bcwr-tflmfsccv46utl4d33w26abar4x3qf25mmn5n7hngdsr5wkuinua",
    "web": "https://replicate.com/p/58bbmgc40drm80cm8yvvwwsv7w"
  },
  "metrics": {
    "predict_time": 7.582019316,
    "total_time": 7.673377
  }
}

Generated in

7.6 seconds

Tweak it Report

free=29090082111488 Downloading weights 2025-01-08T20:59:56Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpe_srp632/weights url=https://replicate.delivery/xezq/N4MICfLsnzyAKCROeM4SiQUWOCu0HxDrtWPVIejfDYEywlMQB/trained_model.tar 2025-01-08T20:59:59Z | INFO | [ Complete ] dest=/tmp/tmpe_srp632/weights size="172 MB" total_elapsed=2.520s url=https://replicate.delivery/xezq/N4MICfLsnzyAKCROeM4SiQUWOCu0HxDrtWPVIejfDYEywlMQB/trained_model.tar Downloaded weights in 2.54s 2025-01-08 20:59:59.439 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/245b1ac6b179a69f 2025-01-08 20:59:59.509 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2025-01-08 20:59:59.510 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-08 20:59:59.510 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 41%|████▏ | 126/304 [00:00<00:00, 1237.22it/s] Applying LoRA: 82%|████████▏ | 250/304 [00:00<00:00, 948.25it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 982.00it/s] 2025-01-08 20:59:59.820 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.38s running quantized prediction Using seed: 40402 0%| | 0/50 [00:00<?, ?it/s] 4%|▍ | 2/50 [00:00<00:02, 18.20it/s] 8%|▊ | 4/50 [00:00<00:03, 13.57it/s] 12%|█▏ | 6/50 [00:00<00:03, 12.53it/s] 16%|█▌ | 8/50 [00:00<00:03, 12.11it/s] 20%|██ | 10/50 [00:00<00:03, 11.85it/s] 24%|██▍ | 12/50 [00:00<00:03, 11.50it/s] 28%|██▊ | 14/50 [00:01<00:03, 11.45it/s] 32%|███▏ | 16/50 [00:01<00:02, 11.46it/s] 36%|███▌ | 18/50 [00:01<00:02, 11.47it/s] 40%|████ | 20/50 [00:01<00:02, 11.46it/s] 44%|████▍ | 22/50 [00:01<00:02, 11.39it/s] 48%|████▊ | 24/50 [00:02<00:02, 11.30it/s] 52%|█████▏ | 26/50 [00:02<00:02, 11.32it/s] 56%|█████▌ | 28/50 [00:02<00:01, 11.37it/s] 60%|██████ | 30/50 [00:02<00:01, 11.41it/s] 64%|██████▍ | 32/50 [00:02<00:01, 11.41it/s] 68%|██████▊ | 34/50 [00:02<00:01, 11.35it/s] 72%|███████▏ | 36/50 [00:03<00:01, 11.33it/s] 76%|███████▌ | 38/50 [00:03<00:01, 11.35it/s] 80%|████████ | 40/50 [00:03<00:00, 11.39it/s] 84%|████████▍ | 42/50 [00:03<00:00, 11.40it/s] 88%|████████▊ | 44/50 [00:03<00:00, 11.38it/s] 92%|█████████▏| 46/50 [00:03<00:00, 11.35it/s] 96%|█████████▌| 48/50 [00:04<00:00, 11.35it/s] 100%|██████████| 50/50 [00:04<00:00, 11.35it/s] 100%|██████████| 50/50 [00:04<00:00, 11.54it/s] Total safe images: 1 out of 1