anotherjesse/sdxl-recur – Run with an API on Replicate

anotherjesse / sdxl-recur

explore img2img zooming sdxl

Cold

Public
1.1K runs
L40S
GitHub

Run with an API

Playground API Examples Train README Versions

Input

prompt

string

Shift + Return to add a new line

Input prompt

Default: "An astronaut riding a rainbow unicorn"

negative_prompt

string

Shift + Return to add a new line

Input Negative Prompt

Default: ""

image

file

instead of starting with txt2img generating the first frame, you can send your own (optional)

width

integer

Width of output image (ignored if image is provided)

Default: 1024

height

integer

Height of output image (ignored if image is provided)

Default: 1024

steps

integer

(minimum: 1, maximum: 500)

Number of denoising steps per image

Default: 10

frames

integer

(minimum: 1, maximum: 500)

Number of frames

Default: 20

zoom

number

(minimum: 1, maximum: 4)

Zoom factor

Default: 1.05

guidance_scale

number

(minimum: 1, maximum: 50)

Scale for classifier-free guidance

Default: 7.5

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

scheduler

string

scheduler

Default: "K_EULER"

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=anotherjesse/sdxl-recur

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 anotherjesse/sdxl-recur using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "anotherjesse/sdxl-recur:dd9bc7346b840bc8902311579728f2af34f4745ee1d36b7afd76a228de1b341c",
  {
    input: {
      zoom: 1.05,
      image: "https://replicate.delivery/pbxt/JfxDhvZy41TsrWdGz4uO5YUpUQkjnndc57u6FQJuAVXl1RHF/moon.jpg",
      steps: 10,
      width: 1024,
      frames: 20,
      height: 1024,
      prompt: "moon rising over clouds and mountains",
      scheduler: "K_EULER",
      guidance_scale: 7.5,
      negative_prompt: "",
      prompt_strength: 0.8
    }
  }
);
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 anotherjesse/sdxl-recur using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "anotherjesse/sdxl-recur:dd9bc7346b840bc8902311579728f2af34f4745ee1d36b7afd76a228de1b341c",
    input={
        "zoom": 1.05,
        "image": "https://replicate.delivery/pbxt/JfxDhvZy41TsrWdGz4uO5YUpUQkjnndc57u6FQJuAVXl1RHF/moon.jpg",
        "steps": 10,
        "width": 1024,
        "frames": 20,
        "height": 1024,
        "prompt": "moon rising over clouds and mountains",
        "scheduler": "K_EULER",
        "guidance_scale": 7.5,
        "negative_prompt": "",
        "prompt_strength": 0.8
    }
)

# The anotherjesse/sdxl-recur model can stream output as it's running.
# The predict method returns an iterator, and you can iterate over that output.
for item in output:
    # https://replicate.com/anotherjesse/sdxl-recur/api#output-schema
    print(item)

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 anotherjesse/sdxl-recur 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": "dd9bc7346b840bc8902311579728f2af34f4745ee1d36b7afd76a228de1b341c",
    "input": {
      "zoom": 1.05,
      "image": "https://replicate.delivery/pbxt/JfxDhvZy41TsrWdGz4uO5YUpUQkjnndc57u6FQJuAVXl1RHF/moon.jpg",
      "steps": 10,
      "width": 1024,
      "frames": 20,
      "height": 1024,
      "prompt": "moon rising over clouds and mountains",
      "scheduler": "K_EULER",
      "guidance_scale": 7.5,
      "negative_prompt": "",
      "prompt_strength": 0.8
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2023-10-10T14:53:27.664546Z",
  "created_at": "2023-10-10T14:52:51.473981Z",
  "data_removed": false,
  "error": null,
  "id": "vv5vw2lbq63wr7hbdx72ow43ne",
  "input": {
    "zoom": 1.05,
    "image": "https://replicate.delivery/pbxt/JfxDhvZy41TsrWdGz4uO5YUpUQkjnndc57u6FQJuAVXl1RHF/moon.jpg",
    "steps": 10,
    "width": 1024,
    "frames": 20,
    "height": 1024,
    "prompt": "moon rising over clouds and mountains",
    "scheduler": "K_EULER",
    "guidance_scale": 7.5,
    "negative_prompt": "",
    "prompt_strength": 0.8
  },
  "logs": "Using seed: 37262\n/usr/local/lib/python3.9/site-packages/torch/nn/modules/conv.py:459: UserWarning: Applied workaround for CuDNN issue, install nvrtc.so (Triggered internally at ../aten/src/ATen/native/cudnn/Conv_v8.cpp:80.)\nreturn F.conv2d(input, weight, bias, self.stride,\n  0%|          | 0/8 [00:00<?, ?it/s]\n 12%|█▎        | 1/8 [00:00<00:01,  6.01it/s]\n 25%|██▌       | 2/8 [00:00<00:00,  6.35it/s]\n 38%|███▊      | 3/8 [00:00<00:00,  6.48it/s]\n 50%|█████     | 4/8 [00:00<00:00,  6.54it/s]\n 62%|██████▎   | 5/8 [00:00<00:00,  6.56it/s]\n 75%|███████▌  | 6/8 [00:00<00:00,  6.58it/s]\n 88%|████████▊ | 7/8 [00:01<00:00,  6.58it/s]\n100%|██████████| 8/8 [00:01<00:00,  6.58it/s]\n100%|██████████| 8/8 [00:01<00:00,  6.53it/s]\n  0%|          | 0/8 [00:00<?, ?it/s]\n 12%|█▎        | 1/8 [00:00<00:01,  6.65it/s]\n 25%|██▌       | 2/8 [00:00<00:00,  6.62it/s]\n 38%|███▊      | 3/8 [00:00<00:00,  6.61it/s]\n 50%|█████     | 4/8 [00:00<00:00,  6.61it/s]\n 62%|██████▎   | 5/8 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  "metrics": {
    "predict_time": 35.052018,
    "total_time": 36.190565
  },
  "output": [
    "https://replicate.delivery/pbxt/VhyqJdVQqnZ5NBhfcmGoi4FXEfx5KKuZ7URplfB1NIUT6iZjA/0000.jpg",
    "https://replicate.delivery/pbxt/CmiH6XTQeo2JAyA3vcvtDC0D5Kx9t97YhetgO4cQ3fIU6iZjA/0001.jpg",
    "https://replicate.delivery/pbxt/FWfgxYK1wsVlZaeMKfw8VaswkTMRHabeWeLKLfTyBDebmuY2IA/0002.jpg",
    "https://replicate.delivery/pbxt/eWgNPUiLGkwATSioOKi0nsO2Qib1oisloxfZkBQeIRod6iZjA/0003.jpg",
    "https://replicate.delivery/pbxt/jWfWsXr8i815HSkEqFbXs9ta0RLMCcnefFkpei28ufR4pLmNC/0004.jpg",
    "https://replicate.delivery/pbxt/Gf6o3KmK3cTPNKrS3XYsM8WyZqgFRFRZZSn6lfs2uwLRdxsRA/0005.jpg",
    "https://replicate.delivery/pbxt/kewn1fsgkgreYJlUed6NyCBlxeb2k41ktmF8pd8G4ATUqLmNC/0006.jpg",
    "https://replicate.delivery/pbxt/rbCENhVAHF7qG9vbosynZPgHIYqAeIIsMQ5TkE0vnVAquY2IA/0007.jpg",
    "https://replicate.delivery/pbxt/Ly2o5QBauSpKDZ6rUSOLxrYTHbMn881AMIHjy4X0DeLruY2IA/0008.jpg",
    "https://replicate.delivery/pbxt/lREuQCqJmFIOIZpvsR77xlMX9efUGVwnI6m3g0XltNzXdxsRA/0009.jpg",
    "https://replicate.delivery/pbxt/JoIpYgeEd0RgHy2FFBFudkzQ5qX9le4p10PIpOUkdq8ZdxsRA/0010.jpg",
    "https://replicate.delivery/pbxt/58oLE3VLId7vDhHM8xjRvCgsM9DaXDL5QU1Vc0Ln6zhWXMbE/0011.jpg",
    "https://replicate.delivery/pbxt/IiVxoYe4lMyXZSi0nCMXKevP3Y5mSAtM2zmxcBVMPpf56iZjA/0012.jpg",
    "https://replicate.delivery/pbxt/ACh9vROTo9KSBVRgF7NH1Ame1vDkT08cjNGOnIwZfYcddxsRA/0013.jpg",
    "https://replicate.delivery/pbxt/3APafV9f3NgQv0qcbHpff5ywbI4N9jLbEiQAk1tPyhdfrLmNC/0014.jpg",
    "https://replicate.delivery/pbxt/Yoaj931WxYpFN9nQpmMsTrzOuMH7MX2gMQWRIoYSloRYXMbE/0015.jpg",
    "https://replicate.delivery/pbxt/1cc8SmFsyq5cLV2Uo3YLahH1wXHkclHoZPczKA7zrBoYXMbE/0016.jpg",
    "https://replicate.delivery/pbxt/PcV4xeVK21SCGCrfnyue8Ti8CqSUtU7P9YgqheHa4aTS2FzGB/0017.jpg",
    "https://replicate.delivery/pbxt/OjkDX05tD7oAI1brzt35Tt2jx3X1OCWVFSDPHnBxJAbZXMbE/0018.jpg",
    "https://replicate.delivery/pbxt/GaxoRfU77xXBGS4hZEFfYszIy5WOpHAzszZc5JyDUn4ndxsRA/0019.jpg"
  ],
  "started_at": "2023-10-10T14:52:52.612528Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/vv5vw2lbq63wr7hbdx72ow43ne",
    "cancel": "https://api.replicate.com/v1/predictions/vv5vw2lbq63wr7hbdx72ow43ne/cancel"
  },
  "version": "9cee5f979f55990d4acb49a9a19553de4d5cedcf0608d1d434e859e734ffb0a8"
}

Generated in

35.1 seconds

Tweak itReport

Using seed: 37262
/usr/local/lib/python3.9/site-packages/torch/nn/modules/conv.py:459: UserWarning: Applied workaround for CuDNN issue, install nvrtc.so (Triggered internally at ../aten/src/ATen/native/cudnn/Conv_v8.cpp:80.)
return F.conv2d(input, weight, bias, self.stride,
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This example was created by a different version, anotherjesse/sdxl-recur:9cee5f97.

Examples

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Run time and cost

This model costs approximately $0.046 to run on Replicate, or 21 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 L40S GPU hardware. Predictions typically complete within 48 seconds. The predict time for this model varies significantly based on the inputs.

Readme

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