doriandarko/lcm-hiroshinagai:b43c25e9 | Run with an API on Replicate

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doriandarko /lcm-hiroshinagai:b43c25e9

Input

prompt

string

Shift + Return to add a new line

In the style of TOK, a car in the countrysideIn the style of TOK, a car in the countryside

Input prompt

Default: "An astronaut riding a rainbow unicorn, cinematic, dramatic"

negative_prompt

string

Shift + Return to add a new line

Input Negative Prompt

Default: ""

image

file

Input image for img2img or inpaint mode

mask

file

Input mask for inpaint mode. Black areas will be preserved, white areas will be inpainted.

width

integer

Width of output image

Default: 1024

height

integer

Height of output image

Default: 1024

num_outputs

integer

(minimum: 1, maximum: 4)

Number of images to output.

Default: 1

scheduler

string

scheduler

Default: "LCM"

num_inference_steps

integer

(minimum: 1, maximum: 20)

Number of denoising steps

Default: 6

guidance_scale

number

(minimum: 1, maximum: 20)

Scale for classifier-free guidance

Default: 2

prompt_strength

number

(minimum: 0, maximum: 1)

Prompt strength when using img2img / inpaint. 1.0 corresponds to full destruction of information in image

Default: 0.8

seed

integer

Random seed. Leave blank to randomize the seed

apply_watermark

boolean

Applies a watermark to enable determining if an image is generated in downstream applications. If you have other provisions for generating or deploying images safely, you can use this to disable watermarking.

Default: true

lora_scale

number

(minimum: 0, maximum: 1)

LoRA additive scale. Only applicable on trained models.

Default: 0.6

disable_safety_checker

boolean

Disable safety checker for generated images. This feature is only available through the API. See [https://replicate.com/docs/how-does-replicate-work#safety](https://replicate.com/docs/how-does-replicate-work#safety)

Default: false

Run this model in Node.js with one line of code:

npx create-replicate --model=doriandarko/lcm-hiroshinagai

or set up a project from scratch

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

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 doriandarko/lcm-hiroshinagai using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "doriandarko/lcm-hiroshinagai:b43c25e9643af233e1258c839b6c6726504cbc25a1843ff80d83d911b8c99faa",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "In the style of TOK, a car in the countryside",
      scheduler: "LCM",
      lora_scale: 0.6,
      num_outputs: 4,
      guidance_scale: 2,
      apply_watermark: true,
      negative_prompt: "black and white, ugly, ",
      prompt_strength: 0.8,
      num_inference_steps: 6
    }
  }
);

// 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=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run doriandarko/lcm-hiroshinagai using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "doriandarko/lcm-hiroshinagai:b43c25e9643af233e1258c839b6c6726504cbc25a1843ff80d83d911b8c99faa",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "In the style of TOK, a car in the countryside",
        "scheduler": "LCM",
        "lora_scale": 0.6,
        "num_outputs": 4,
        "guidance_scale": 2,
        "apply_watermark": True,
        "negative_prompt": "black and white, ugly, ",
        "prompt_strength": 0.8,
        "num_inference_steps": 6
    }
)
print(output)

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=<paste-your-token-here>

Find your API token in your account settings.

Run doriandarko/lcm-hiroshinagai 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": "doriandarko/lcm-hiroshinagai:b43c25e9643af233e1258c839b6c6726504cbc25a1843ff80d83d911b8c99faa",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "In the style of TOK, a car in the countryside",
      "scheduler": "LCM",
      "lora_scale": 0.6,
      "num_outputs": 4,
      "guidance_scale": 2,
      "apply_watermark": true,
      "negative_prompt": "black and white, ugly, ",
      "prompt_strength": 0.8,
      "num_inference_steps": 6
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2023-11-15T05:16:34.537473Z",
  "created_at": "2023-11-15T05:16:18.166860Z",
  "data_removed": false,
  "error": null,
  "id": "pbnkr4tbfqd3pahwxyfv3ab24a",
  "input": {
    "width": 1024,
    "height": 1024,
    "prompt": "In the style of TOK, a car in the countryside",
    "scheduler": "LCM",
    "lora_scale": 0.6,
    "num_outputs": 4,
    "guidance_scale": 2,
    "apply_watermark": true,
    "negative_prompt": "black and white, ugly, ",
    "prompt_strength": 0.8,
    "num_inference_steps": 6
  },
  "logs": "Using seed: 48493\nEnsuring enough disk space...\nFree disk space: 1429398622208\nDownloading weights: https://replicate.delivery/pbxt/2qPgVBQfv02WJapYb0CrvfE0tEPGSWInWTo3Of2QTKDZZAxjA/trained_model.tar\nb'Downloaded 186 MB bytes in 0.660s (282 MB/s)\\nExtracted 186 MB in 0.065s (2.9 GB/s)\\n'\nDownloaded weights in 0.9539430141448975 seconds\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: In the style of <s0><s1>, a car in the countryside\ntxt2img mode\nThe config attributes {'skip_prk_steps': True} were passed to LCMScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file.\n  0%|          | 0/6 [00:00<?, ?it/s]/root/.pyenv/versions/3.10.13/lib/python3.10/site-packages/diffusers/models/attention_processor.py:1821: FutureWarning: `LoRAAttnProcessor2_0` is deprecated and will be removed in version 0.26.0. Make sure use AttnProcessor2_0 instead by settingLoRA layers to `self.{to_q,to_k,to_v,to_out[0]}.lora_layer` respectively. This will be done automatically when using `LoraLoaderMixin.load_lora_weights`\ndeprecate(\n 17%|█▋        | 1/6 [00:01<00:05,  1.13s/it]\n 33%|███▎      | 2/6 [00:02<00:04,  1.04s/it]\n 50%|█████     | 3/6 [00:03<00:03,  1.02s/it]\n 67%|██████▋   | 4/6 [00:04<00:02,  1.01s/it]\n 83%|████████▎ | 5/6 [00:05<00:00,  1.00it/s]\n100%|██████████| 6/6 [00:06<00:00,  1.00it/s]\n100%|██████████| 6/6 [00:06<00:00,  1.01s/it]",
  "metrics": {
    "predict_time": 14.691208,
    "total_time": 16.370613
  },
  "output": [
    "https://replicate.delivery/pbxt/90BuEtogj0qtJJhLnL7S1QDh0Yc2VoKWTIU4y1e9fUzvYg4RA/out-0.png",
    "https://replicate.delivery/pbxt/bJnt9cRo1trePqWQnmrTMLip6XCDG3PU1nIkfQ8TyT4xYg4RA/out-1.png",
    "https://replicate.delivery/pbxt/222CgQeIeImZB0OqmH5JTLjS5F8oW5NDfit1vT0UlOljxAxjA/out-2.png",
    "https://replicate.delivery/pbxt/WZzbeAUZbQWDQCGPzppipFABshrtEEcrmVcWSaBH24HZMQ8IA/out-3.png"
  ],
  "started_at": "2023-11-15T05:16:19.846265Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/pbnkr4tbfqd3pahwxyfv3ab24a",
    "cancel": "https://api.replicate.com/v1/predictions/pbnkr4tbfqd3pahwxyfv3ab24a/cancel"
  },
  "version": "b43c25e9643af233e1258c839b6c6726504cbc25a1843ff80d83d911b8c99faa"
}

Generated in

14.7 seconds

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