Prediction

Model

prompthunt/cog-sdxl-controlnet-inference:c748f859

723p4ldb2m6qgp47s5uydlunou

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

14.1s

Created

about 2 years ago by prompthunt

Webhook

–

Input

lora_weights: https://replicate.delivery/pbxt/yuebGYwbnLUIbiFtTk4tjkkO2BJMcPheYILs7vy7MnzMpB5RA/trained_model.tar
prompt: ((Moody portrait)) of TOK man wearing glasses dressed in arctic fashion against an arctic backdrop with iceberg influences, perfect eyes
negative_prompt: defined jawline, plastic, blurry, grainy, [deformed | disfigured], poorly drawn, [bad : wrong] anatomy, [extra | missing | floating | disconnected] limb, (mutated hands and fingers), blurry
image: https://replicate.delivery/pbxt/JtBXIeco0ymI5gPV7hbpb3N8gjPGQePmadfUmXV6njkeM7E9/w1024.jpeg
width: 1024
height: 1024
num_outputs: 1
scheduler: K_EULER
num_inference_steps: 25
guidance_scale: 3
prompt_strength: 0.8
seed: 1234
refine: no_refiner
high_noise_frac: 0.8
apply_watermark: true
lora_scale: 0.6
controlnet_conditioning_scale: 0.5
controlnet_start: 0
controlnet_end: 1

{
  "apply_watermark": true,
  "controlnet_conditioning_scale": 0.5,
  "controlnet_end": 1,
  "controlnet_start": 0,
  "guidance_scale": 3,
  "height": 1024,
  "high_noise_frac": 0.8,
  "image": "https://replicate.delivery/pbxt/JtBXIeco0ymI5gPV7hbpb3N8gjPGQePmadfUmXV6njkeM7E9/w1024.jpeg",
  "lora_scale": 0.6,
  "lora_weights": "https://replicate.delivery/pbxt/yuebGYwbnLUIbiFtTk4tjkkO2BJMcPheYILs7vy7MnzMpB5RA/trained_model.tar",
  "negative_prompt": "defined jawline, plastic, blurry, grainy, [deformed | disfigured], poorly drawn, [bad : wrong] anatomy, [extra | missing | floating | disconnected] limb, (mutated hands and fingers), blurry",
  "num_inference_steps": 25,
  "num_outputs": 1,
  "prompt": "((Moody portrait)) of TOK man wearing glasses dressed in arctic fashion against an arctic backdrop with iceberg influences, perfect eyes",
  "prompt_strength": 0.8,
  "refine": "no_refiner",
  "scheduler": "K_EULER",
  "seed": 1234,
  "width": 1024
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_eME**********************************

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 prompthunt/cog-sdxl-controlnet-inference using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "prompthunt/cog-sdxl-controlnet-inference:c748f859defb73fe0679ce88bf56c8c203cd9bbe4e81be20325ad65c041a7641",
  {
    input: {
      apply_watermark: true,
      controlnet_conditioning_scale: 0.5,
      controlnet_end: 1,
      controlnet_start: 0,
      guidance_scale: 3,
      height: 1024,
      high_noise_frac: 0.8,
      image: "https://replicate.delivery/pbxt/JtBXIeco0ymI5gPV7hbpb3N8gjPGQePmadfUmXV6njkeM7E9/w1024.jpeg",
      lora_scale: 0.6,
      lora_weights: "https://replicate.delivery/pbxt/yuebGYwbnLUIbiFtTk4tjkkO2BJMcPheYILs7vy7MnzMpB5RA/trained_model.tar",
      negative_prompt: "defined jawline, plastic, blurry, grainy, [deformed | disfigured], poorly drawn, [bad : wrong] anatomy, [extra | missing | floating | disconnected] limb, (mutated hands and fingers), blurry",
      num_inference_steps: 25,
      num_outputs: 1,
      prompt: "((Moody portrait)) of TOK man wearing glasses dressed in arctic fashion against an arctic backdrop with iceberg influences, perfect eyes",
      prompt_strength: 0.8,
      refine: "no_refiner",
      scheduler: "K_EULER",
      seed: 1234,
      width: 1024
    }
  }
);

// 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_eME**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

Run prompthunt/cog-sdxl-controlnet-inference using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "prompthunt/cog-sdxl-controlnet-inference:c748f859defb73fe0679ce88bf56c8c203cd9bbe4e81be20325ad65c041a7641",
    input={
        "apply_watermark": True,
        "controlnet_conditioning_scale": 0.5,
        "controlnet_end": 1,
        "controlnet_start": 0,
        "guidance_scale": 3,
        "height": 1024,
        "high_noise_frac": 0.8,
        "image": "https://replicate.delivery/pbxt/JtBXIeco0ymI5gPV7hbpb3N8gjPGQePmadfUmXV6njkeM7E9/w1024.jpeg",
        "lora_scale": 0.6,
        "lora_weights": "https://replicate.delivery/pbxt/yuebGYwbnLUIbiFtTk4tjkkO2BJMcPheYILs7vy7MnzMpB5RA/trained_model.tar",
        "negative_prompt": "defined jawline, plastic, blurry, grainy, [deformed | disfigured], poorly drawn, [bad : wrong] anatomy, [extra | missing | floating | disconnected] limb, (mutated hands and fingers), blurry",
        "num_inference_steps": 25,
        "num_outputs": 1,
        "prompt": "((Moody portrait)) of TOK man wearing glasses dressed in arctic fashion against an arctic backdrop with iceberg influences, perfect eyes",
        "prompt_strength": 0.8,
        "refine": "no_refiner",
        "scheduler": "K_EULER",
        "seed": 1234,
        "width": 1024
    }
)

# 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_eME**********************************

This is your API token. Keep it to yourself.

Run prompthunt/cog-sdxl-controlnet-inference 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": "prompthunt/cog-sdxl-controlnet-inference:c748f859defb73fe0679ce88bf56c8c203cd9bbe4e81be20325ad65c041a7641",
    "input": {
      "apply_watermark": true,
      "controlnet_conditioning_scale": 0.5,
      "controlnet_end": 1,
      "controlnet_start": 0,
      "guidance_scale": 3,
      "height": 1024,
      "high_noise_frac": 0.8,
      "image": "https://replicate.delivery/pbxt/JtBXIeco0ymI5gPV7hbpb3N8gjPGQePmadfUmXV6njkeM7E9/w1024.jpeg",
      "lora_scale": 0.6,
      "lora_weights": "https://replicate.delivery/pbxt/yuebGYwbnLUIbiFtTk4tjkkO2BJMcPheYILs7vy7MnzMpB5RA/trained_model.tar",
      "negative_prompt": "defined jawline, plastic, blurry, grainy, [deformed | disfigured], poorly drawn, [bad : wrong] anatomy, [extra | missing | floating | disconnected] limb, (mutated hands and fingers), blurry",
      "num_inference_steps": 25,
      "num_outputs": 1,
      "prompt": "((Moody portrait)) of TOK man wearing glasses dressed in arctic fashion against an arctic backdrop with iceberg influences, perfect eyes",
      "prompt_strength": 0.8,
      "refine": "no_refiner",
      "scheduler": "K_EULER",
      "seed": 1234,
      "width": 1024
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "id": "723p4ldb2m6qgp47s5uydlunou",
  "model": "prompthunt/cog-sdxl-controlnet-inference",
  "version": "c748f859defb73fe0679ce88bf56c8c203cd9bbe4e81be20325ad65c041a7641",
  "input": {
    "apply_watermark": true,
    "controlnet_conditioning_scale": 0.5,
    "controlnet_end": 1,
    "controlnet_start": 0,
    "guidance_scale": 3,
    "height": 1024,
    "high_noise_frac": 0.8,
    "image": "https://replicate.delivery/pbxt/JtBXIeco0ymI5gPV7hbpb3N8gjPGQePmadfUmXV6njkeM7E9/w1024.jpeg",
    "lora_scale": 0.6,
    "lora_weights": "https://replicate.delivery/pbxt/yuebGYwbnLUIbiFtTk4tjkkO2BJMcPheYILs7vy7MnzMpB5RA/trained_model.tar",
    "negative_prompt": "defined jawline, plastic, blurry, grainy, [deformed | disfigured], poorly drawn, [bad : wrong] anatomy, [extra | missing | floating | disconnected] limb, (mutated hands and fingers), blurry",
    "num_inference_steps": 25,
    "num_outputs": 1,
    "prompt": "((Moody portrait)) of TOK man wearing glasses dressed in arctic fashion against an arctic backdrop with iceberg influences, perfect eyes",
    "prompt_strength": 0.8,
    "refine": "no_refiner",
    "scheduler": "K_EULER",
    "seed": 1234,
    "width": 1024
  },
  "logs": "Using seed: 1234\nLoading sdxl txt2img pipeline...\nLoading pipeline components...:   0%|          | 0/7 [00:00<?, ?it/s]\nLoading pipeline components...:  29%|██▊       | 2/7 [00:00<00:00,  6.99it/s]\nLoading pipeline components...:  57%|█████▋    | 4/7 [00:00<00:00,  6.95it/s]\nLoading pipeline components...:  86%|████████▌ | 6/7 [00:01<00:00,  5.11it/s]\nLoading pipeline components...: 100%|██████████| 7/7 [00:01<00:00,  6.08it/s]\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nLoading SDXL img2img pipeline...\nLoading SDXL inpaint pipeline...\nLoading controlnet model\nimg2img mode\nPrompt: ((Moody portrait)) of <s0><s1> man wearing glasses dressed in arctic fashion against an arctic backdrop with iceberg influences, perfect eyes\n  0%|          | 0/20 [00:00<?, ?it/s]\n  5%|▌         | 1/20 [00:00<00:05,  3.69it/s]\n 10%|█         | 2/20 [00:00<00:04,  3.68it/s]\n 15%|█▌        | 3/20 [00:00<00:04,  3.68it/s]\n 20%|██        | 4/20 [00:01<00:04,  3.67it/s]\n 25%|██▌       | 5/20 [00:01<00:04,  3.67it/s]\n 30%|███       | 6/20 [00:01<00:03,  3.67it/s]\n 35%|███▌      | 7/20 [00:01<00:03,  3.68it/s]\n 40%|████      | 8/20 [00:02<00:03,  3.68it/s]\n 45%|████▌     | 9/20 [00:02<00:02,  3.68it/s]\n 50%|█████     | 10/20 [00:02<00:02,  3.68it/s]\n 55%|█████▌    | 11/20 [00:02<00:02,  3.68it/s]\n 60%|██████    | 12/20 [00:03<00:02,  3.68it/s]\n 65%|██████▌   | 13/20 [00:03<00:01,  3.68it/s]\n 70%|███████   | 14/20 [00:03<00:01,  3.68it/s]\n 75%|███████▌  | 15/20 [00:04<00:01,  3.68it/s]\n 80%|████████  | 16/20 [00:04<00:01,  3.68it/s]\n 85%|████████▌ | 17/20 [00:04<00:00,  3.68it/s]\n 90%|█████████ | 18/20 [00:04<00:00,  3.68it/s]\n 95%|█████████▌| 19/20 [00:05<00:00,  3.68it/s]\n100%|██████████| 20/20 [00:05<00:00,  3.68it/s]\n100%|██████████| 20/20 [00:05<00:00,  3.68it/s]",
  "output": [
    "https://replicate.delivery/pbxt/bEf9XAvle3vSckOAyTBXmMSOYIqbf0jdgDGbtKTCKVAVcHyjA/out-0.png"
  ],
  "data_removed": false,
  "error": null,
  "source": "web",
  "status": "succeeded",
  "created_at": "2023-11-16T21:28:29.220765Z",
  "started_at": "2023-11-16T21:28:29.276322Z",
  "completed_at": "2023-11-16T21:28:43.33115Z",
  "urls": {
    "cancel": "https://api.replicate.com/v1/predictions/723p4ldb2m6qgp47s5uydlunou/cancel",
    "get": "https://api.replicate.com/v1/predictions/723p4ldb2m6qgp47s5uydlunou"
  },
  "metrics": {
    "predict_time": 14.054828,
    "total_time": 14.110385
  }
}

Generated in

14.1 seconds

Tweak it Report

Using seed: 1234 Loading sdxl txt2img pipeline... Loading pipeline components...: 0%| | 0/7 [00:00<?, ?it/s] Loading pipeline components...: 29%|██▊ | 2/7 [00:00<00:00, 6.99it/s] Loading pipeline components...: 57%|█████▋ | 4/7 [00:00<00:00, 6.95it/s] Loading pipeline components...: 86%|████████▌ | 6/7 [00:01<00:00, 5.11it/s] Loading pipeline components...: 100%|██████████| 7/7 [00:01<00:00, 6.08it/s] Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Loading SDXL img2img pipeline... Loading SDXL inpaint pipeline... Loading controlnet model img2img mode Prompt: ((Moody portrait)) of <s0><s1> man wearing glasses dressed in arctic fashion against an arctic backdrop with iceberg influences, perfect eyes 0%| | 0/20 [00:00<?, ?it/s] 5%|▌ | 1/20 [00:00<00:05, 3.69it/s] 10%|█ | 2/20 [00:00<00:04, 3.68it/s] 15%|█▌ | 3/20 [00:00<00:04, 3.68it/s] 20%|██ | 4/20 [00:01<00:04, 3.67it/s] 25%|██▌ | 5/20 [00:01<00:04, 3.67it/s] 30%|███ | 6/20 [00:01<00:03, 3.67it/s] 35%|███▌ | 7/20 [00:01<00:03, 3.68it/s] 40%|████ | 8/20 [00:02<00:03, 3.68it/s] 45%|████▌ | 9/20 [00:02<00:02, 3.68it/s] 50%|█████ | 10/20 [00:02<00:02, 3.68it/s] 55%|█████▌ | 11/20 [00:02<00:02, 3.68it/s] 60%|██████ | 12/20 [00:03<00:02, 3.68it/s] 65%|██████▌ | 13/20 [00:03<00:01, 3.68it/s] 70%|███████ | 14/20 [00:03<00:01, 3.68it/s] 75%|███████▌ | 15/20 [00:04<00:01, 3.68it/s] 80%|████████ | 16/20 [00:04<00:01, 3.68it/s] 85%|████████▌ | 17/20 [00:04<00:00, 3.68it/s] 90%|█████████ | 18/20 [00:04<00:00, 3.68it/s] 95%|█████████▌| 19/20 [00:05<00:00, 3.68it/s] 100%|██████████| 20/20 [00:05<00:00, 3.68it/s] 100%|██████████| 20/20 [00:05<00:00, 3.68it/s]