cloneofsimo/fad_v0_lora – Run with an API on Replicate

Input

prompt

string

Shift + Return to add a new line

a man riding his bike down the city streets of japan, magic houra man riding his bike down the city streets of japan, magic hour

Input prompt. Use <1>, <2>, <3>, etc., to specify LoRA concepts

Default: "a photo of <1> riding a horse on mars"

negative_prompt

string

Shift + Return to add a new line

Specify things to not see in the output

Default: ""

width

integer

Width of output image. Maximum size is 1024x768 or 768x1024 because of memory limits

Default: 512

height

integer

Height of output image. Maximum size is 1024x768 or 768x1024 because of memory limits

Default: 512

num_outputs

integer

(minimum: 1, maximum: 4)

Number of images to output.

Default: 1

num_inference_steps

integer

(minimum: 1, maximum: 500)

Number of denoising steps

Default: 50

guidance_scale

number

(minimum: 1, maximum: 20)

Scale for classifier-free guidance

Default: 7.5

scheduler

string

Choose a scheduler.

Default: "DPMSolverMultistep"

lora_urls

string

Shift + Return to add a new line

List of urls for safetensors of lora models, seperated with | .

Default: ""

lora_scales

string

Shift + Return to add a new line

List of scales for safetensors of lora models, seperated with |

Default: "0.5"

seed

integer

Random seed. Leave blank to randomize the seed

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

npx create-replicate --model=cloneofsimo/fad_v0_lora

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";

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

Run cloneofsimo/fad_v0_lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "cloneofsimo/fad_v0_lora:c1e671c76f6f833c392337c7f411f89777148dbabf973decff3809c47229d9b0",
  {
    input: {
      width: 512,
      height: 768,
      prompt: "a man riding his bike down the city streets of japan, magic hour",
      lora_urls: "",
      scheduler: "DPMSolverMultistep",
      lora_scales: "0.5",
      num_outputs: 1,
      guidance_scale: 4,
      negative_prompt: "",
      num_inference_steps: 50
    }
  }
);
console.log(output);

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 cloneofsimo/fad_v0_lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "cloneofsimo/fad_v0_lora:c1e671c76f6f833c392337c7f411f89777148dbabf973decff3809c47229d9b0",
    input={
        "width": 512,
        "height": 768,
        "prompt": "a man riding his bike down the city streets of japan, magic hour",
        "lora_urls": "",
        "scheduler": "DPMSolverMultistep",
        "lora_scales": "0.5",
        "num_outputs": 1,
        "guidance_scale": 4,
        "negative_prompt": "",
        "num_inference_steps": 50
    }
)
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 cloneofsimo/fad_v0_lora 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": "c1e671c76f6f833c392337c7f411f89777148dbabf973decff3809c47229d9b0",
    "input": {
      "width": 512,
      "height": 768,
      "prompt": "a man riding his bike down the city streets of japan, magic hour",
      "lora_urls": "",
      "scheduler": "DPMSolverMultistep",
      "lora_scales": "0.5",
      "num_outputs": 1,
      "guidance_scale": 4,
      "negative_prompt": "",
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

You can run this model locally using Cog. First, install Cog:

brew install cog

If you don’t have Homebrew, there are other installation options available.

Run this to download the model and run it in your local environment:

cog predict r8.im/cloneofsimo/fad_v0_lora@sha256:c1e671c76f6f833c392337c7f411f89777148dbabf973decff3809c47229d9b0 \
  -i 'width=512' \
  -i 'height=768' \
  -i 'prompt="a man riding his bike down the city streets of japan, magic hour"' \
  -i 'lora_urls=""' \
  -i 'scheduler="DPMSolverMultistep"' \
  -i 'lora_scales="0.5"' \
  -i 'num_outputs=1' \
  -i 'guidance_scale=4' \
  -i 'negative_prompt=""' \
  -i 'num_inference_steps=50'

To learn more, take a look at the Cog documentation.

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 --gpus=all r8.im/cloneofsimo/fad_v0_lora@sha256:c1e671c76f6f833c392337c7f411f89777148dbabf973decff3809c47229d9b0
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "width": 512,
      "height": 768,
      "prompt": "a man riding his bike down the city streets of japan, magic hour",
      "lora_urls": "",
      "scheduler": "DPMSolverMultistep",
      "lora_scales": "0.5",
      "num_outputs": 1,
      "guidance_scale": 4,
      "negative_prompt": "",
      "num_inference_steps": 50
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

{
  "completed_at": "2023-02-12T07:08:51.143538Z",
  "created_at": "2023-02-12T07:08:44.719268Z",
  "data_removed": false,
  "error": null,
  "id": "bpqodotkorgtbf5qvmimpjfnzi",
  "input": {
    "width": 512,
    "height": "768",
    "prompt": "a man riding his bike down the city streets of japan, magic hour",
    "scheduler": "DPMSolverMultistep",
    "num_outputs": 1,
    "guidance_scale": "4.0",
    "num_inference_steps": 50
  },
  "logs": "Using seed: 39270\nNo LoRA models provided, using default model...\n  0%|          | 0/50 [00:00<?, ?it/s]\n  4%|▍         | 2/50 [00:00<00:03, 12.46it/s]\n  8%|▊         | 4/50 [00:00<00:03, 13.06it/s]\n 12%|█▏        | 6/50 [00:00<00:03, 13.45it/s]\n 16%|█▌        | 8/50 [00:00<00:03, 13.64it/s]\n 20%|██        | 10/50 [00:00<00:02, 13.69it/s]\n 24%|██▍       | 12/50 [00:00<00:02, 13.71it/s]\n 28%|██▊       | 14/50 [00:01<00:02, 13.74it/s]\n 32%|███▏      | 16/50 [00:01<00:02, 13.82it/s]\n 36%|███▌      | 18/50 [00:01<00:02, 13.77it/s]\n 40%|████      | 20/50 [00:01<00:02, 13.78it/s]\n 44%|████▍     | 22/50 [00:01<00:02, 13.79it/s]\n 48%|████▊     | 24/50 [00:01<00:01, 13.86it/s]\n 52%|█████▏    | 26/50 [00:01<00:01, 13.87it/s]\n 56%|█████▌    | 28/50 [00:02<00:01, 13.86it/s]\n 60%|██████    | 30/50 [00:02<00:01, 13.82it/s]\n 64%|██████▍   | 32/50 [00:02<00:01, 13.77it/s]\n 68%|██████▊   | 34/50 [00:02<00:01, 13.67it/s]\n 72%|███████▏  | 36/50 [00:02<00:01, 13.65it/s]\n 76%|███████▌  | 38/50 [00:02<00:00, 13.74it/s]\n 80%|████████  | 40/50 [00:02<00:00, 13.76it/s]\n 84%|████████▍ | 42/50 [00:03<00:00, 13.75it/s]\n 88%|████████▊ | 44/50 [00:03<00:00, 13.72it/s]\n 92%|█████████▏| 46/50 [00:03<00:00, 13.67it/s]\n 96%|█████████▌| 48/50 [00:03<00:00, 13.71it/s]\n100%|██████████| 50/50 [00:03<00:00, 13.65it/s]\n100%|██████████| 50/50 [00:03<00:00, 13.70it/s]",
  "metrics": {
    "predict_time": 6.365065,
    "total_time": 6.42427
  },
  "output": [
    "https://replicate.delivery/pbxt/fSaTPTVgwDwGDie7QFVjjlHQ1ryOu5T8uUuwGqSZ6FPCKkdQA/out-0.png"
  ],
  "started_at": "2023-02-12T07:08:44.778473Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/bpqodotkorgtbf5qvmimpjfnzi",
    "cancel": "https://api.replicate.com/v1/predictions/bpqodotkorgtbf5qvmimpjfnzi/cancel"
  },
  "version": "694fa248ecf0f4de0c138b6e2267f2a15c51185463e84734962f7620502bb01c"
}

Generated in

6.4 seconds

Tweak itReport

This example was created by a different version, cloneofsimo/fad_v0_lora:694fa248.

Run time and cost

This model costs approximately $0.017 to run on Replicate, or 58 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia A100 (80GB) GPU hardware. Predictions typically complete within 12 seconds.