camenduru / renoise-inversion

{
  "Labmda_AC": 20,
  "Input_Image": "https://replicate.delivery/pbxt/Kc7elOyRLky80eMlw7oKJXrvOfXNa8GF5LXuC9PLneZNH7qi/kitten.jpg",
  "Source_Prompt": "A kitten is sitting in a basket on a branch",
  "Target_Prompt": "a lego kitten is sitting in a basket on a branch",
  "Labmda_Patch_KL": 0.065,
  "Inversion_Strength": 1,
  "Preform_Noise_Correction": true,
  "Number_of_ReNoise_Iterations": 1,
  "Preform_Estimation_Averaging": true,
  "Last_Estimation_in_Average_T_G": 10,
  "Last_Estimation_in_Average_T_L": 5,
  "First_Estimation_in_Average_T_G": 8,
  "First_Estimation_in_Average_T_L": 0,
  "Denoise_Classifier_Free_Guidence_Scale": 1
}

Install Replicate’s Node.js client library:

npm install replicate

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 camenduru/renoise-inversion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "camenduru/renoise-inversion:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a",
  {
    input: {
      Labmda_AC: 20,
      Input_Image: "https://replicate.delivery/pbxt/Kc7elOyRLky80eMlw7oKJXrvOfXNa8GF5LXuC9PLneZNH7qi/kitten.jpg",
      Source_Prompt: "A kitten is sitting in a basket on a branch",
      Target_Prompt: "a lego kitten is sitting in a basket on a branch",
      Labmda_Patch_KL: 0.065,
      Inversion_Strength: 1,
      Preform_Noise_Correction: true,
      Number_of_ReNoise_Iterations: 1,
      Preform_Estimation_Averaging: true,
      Last_Estimation_in_Average_T_G: 10,
      Last_Estimation_in_Average_T_L: 5,
      First_Estimation_in_Average_T_G: 8,
      First_Estimation_in_Average_T_L: 0,
      Denoise_Classifier_Free_Guidence_Scale: 1
    }
  }
);

// To access the file URL:
console.log(output.url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", 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

Import the client:

import replicate

Run camenduru/renoise-inversion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "camenduru/renoise-inversion:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a",
    input={
        "Labmda_AC": 20,
        "Input_Image": "https://replicate.delivery/pbxt/Kc7elOyRLky80eMlw7oKJXrvOfXNa8GF5LXuC9PLneZNH7qi/kitten.jpg",
        "Source_Prompt": "A kitten is sitting in a basket on a branch",
        "Target_Prompt": "a lego kitten is sitting in a basket on a branch",
        "Labmda_Patch_KL": 0.065,
        "Inversion_Strength": 1,
        "Preform_Noise_Correction": True,
        "Number_of_ReNoise_Iterations": 1,
        "Preform_Estimation_Averaging": True,
        "Last_Estimation_in_Average_T_G": 10,
        "Last_Estimation_in_Average_T_L": 5,
        "First_Estimation_in_Average_T_G": 8,
        "First_Estimation_in_Average_T_L": 0,
        "Denoise_Classifier_Free_Guidence_Scale": 1
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Run camenduru/renoise-inversion 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": "camenduru/renoise-inversion:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a",
    "input": {
      "Labmda_AC": 20,
      "Input_Image": "https://replicate.delivery/pbxt/Kc7elOyRLky80eMlw7oKJXrvOfXNa8GF5LXuC9PLneZNH7qi/kitten.jpg",
      "Source_Prompt": "A kitten is sitting in a basket on a branch",
      "Target_Prompt": "a lego kitten is sitting in a basket on a branch",
      "Labmda_Patch_KL": 0.065,
      "Inversion_Strength": 1,
      "Preform_Noise_Correction": true,
      "Number_of_ReNoise_Iterations": 1,
      "Preform_Estimation_Averaging": true,
      "Last_Estimation_in_Average_T_G": 10,
      "Last_Estimation_in_Average_T_L": 5,
      "First_Estimation_in_Average_T_G": 8,
      "First_Estimation_in_Average_T_L": 0,
      "Denoise_Classifier_Free_Guidence_Scale": 1
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2024-03-22T11:54:54.372078Z",
  "created_at": "2024-03-22T11:52:18.732504Z",
  "data_removed": false,
  "error": null,
  "id": "f3qx56lb6uokdnow4i6gy27wpm",
  "input": {
    "Labmda_AC": 20,
    "Input_Image": "https://replicate.delivery/pbxt/Kc7elOyRLky80eMlw7oKJXrvOfXNa8GF5LXuC9PLneZNH7qi/kitten.jpg",
    "Source_Prompt": "A kitten is sitting in a basket on a branch",
    "Target_Prompt": "a lego kitten is sitting in a basket on a branch",
    "Labmda_Patch_KL": 0.065,
    "Inversion_Strength": 1,
    "Preform_Noise_Correction": true,
    "Number_of_ReNoise_Iterations": 1,
    "Preform_Estimation_Averaging": true,
    "Last_Estimation_in_Average_T_G": 10,
    "Last_Estimation_in_Average_T_L": 5,
    "First_Estimation_in_Average_T_G": 8,
    "First_Estimation_in_Average_T_L": 0,
    "Denoise_Classifier_Free_Guidence_Scale": 1
  },
  "logs": "Inverting...\n  0%|          | 0/4 [00:00<?, ?it/s]\n 25%|██▌       | 1/4 [00:01<00:03,  1.09s/it]\n 50%|█████     | 2/4 [00:01<00:01,  1.63it/s]\n 75%|███████▌  | 3/4 [00:01<00:00,  2.34it/s]\n100%|██████████| 4/4 [00:01<00:00,  2.98it/s]\n100%|██████████| 4/4 [00:01<00:00,  2.26it/s]\nGenerating...\n  0%|          | 0/4 [00:00<?, ?it/s]\n 50%|█████     | 2/4 [00:00<00:00, 15.21it/s]\n100%|██████████| 4/4 [00:00<00:00, 15.44it/s]\n100%|██████████| 4/4 [00:00<00:00, 15.38it/s]\nPopping cache",
  "metrics": {
    "predict_time": 4.718288,
    "total_time": 155.639574
  },
  "output": "https://replicate.delivery/pbxt/rKIofC19lwRwWKy3ToHKBixqMbvTVy8eY4Y6nygPDo8NOyiSA/image.png",
  "started_at": "2024-03-22T11:54:49.653790Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/f3qx56lb6uokdnow4i6gy27wpm",
    "cancel": "https://api.replicate.com/v1/predictions/f3qx56lb6uokdnow4i6gy27wpm/cancel"
  },
  "version": "bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a"
}

Generated in

4.7 seconds

Tweak it ShareReport

Prediction

camenduru/renoise-inversion:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a

Model

camenduru/renoise-inversion:bcd108aa

znh2a5lbxpx4ybgyzsgxlozt3u

Status

Succeeded

Source

Web

Hardware

A40

Total duration

3m 33s

Created

about 1 year ago

Input

Labmda_AC: 20
Input_Image
Source_Prompt: A kitten is sitting in a basket on a branch
Target_Prompt: a brokkoli is sitting in a basket on a branch
Labmda_Patch_KL: 0.065
Inversion_Strength: 1
Preform_Noise_Correction
Number_of_ReNoise_Iterations: 1
Preform_Estimation_Averaging
Last_Estimation_in_Average_T_G: 10
Last_Estimation_in_Average_T_L: 5
First_Estimation_in_Average_T_G: 8
First_Estimation_in_Average_T_L: 0
Denoise_Classifier_Free_Guidence_Scale: 1

{
  "Labmda_AC": 20,
  "Input_Image": "https://replicate.delivery/pbxt/Kc7elOyRLky80eMlw7oKJXrvOfXNa8GF5LXuC9PLneZNH7qi/kitten.jpg",
  "Source_Prompt": "A kitten is sitting in a basket on a branch",
  "Target_Prompt": "a brokkoli is sitting in a basket on a branch",
  "Labmda_Patch_KL": 0.065,
  "Inversion_Strength": 1,
  "Preform_Noise_Correction": true,
  "Number_of_ReNoise_Iterations": 1,
  "Preform_Estimation_Averaging": true,
  "Last_Estimation_in_Average_T_G": 10,
  "Last_Estimation_in_Average_T_L": 5,
  "First_Estimation_in_Average_T_G": 8,
  "First_Estimation_in_Average_T_L": 0,
  "Denoise_Classifier_Free_Guidence_Scale": 1
}

Install Replicate’s Node.js client library:

npm install replicate

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 camenduru/renoise-inversion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "camenduru/renoise-inversion:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a",
  {
    input: {
      Labmda_AC: 20,
      Input_Image: "https://replicate.delivery/pbxt/Kc7elOyRLky80eMlw7oKJXrvOfXNa8GF5LXuC9PLneZNH7qi/kitten.jpg",
      Source_Prompt: "A kitten is sitting in a basket on a branch",
      Target_Prompt: "a brokkoli is sitting in a basket on a branch",
      Labmda_Patch_KL: 0.065,
      Inversion_Strength: 1,
      Preform_Noise_Correction: true,
      Number_of_ReNoise_Iterations: 1,
      Preform_Estimation_Averaging: true,
      Last_Estimation_in_Average_T_G: 10,
      Last_Estimation_in_Average_T_L: 5,
      First_Estimation_in_Average_T_G: 8,
      First_Estimation_in_Average_T_L: 0,
      Denoise_Classifier_Free_Guidence_Scale: 1
    }
  }
);

// To access the file URL:
console.log(output.url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", 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

Import the client:

import replicate

Run camenduru/renoise-inversion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "camenduru/renoise-inversion:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a",
    input={
        "Labmda_AC": 20,
        "Input_Image": "https://replicate.delivery/pbxt/Kc7elOyRLky80eMlw7oKJXrvOfXNa8GF5LXuC9PLneZNH7qi/kitten.jpg",
        "Source_Prompt": "A kitten is sitting in a basket on a branch",
        "Target_Prompt": "a brokkoli is sitting in a basket on a branch",
        "Labmda_Patch_KL": 0.065,
        "Inversion_Strength": 1,
        "Preform_Noise_Correction": True,
        "Number_of_ReNoise_Iterations": 1,
        "Preform_Estimation_Averaging": True,
        "Last_Estimation_in_Average_T_G": 10,
        "Last_Estimation_in_Average_T_L": 5,
        "First_Estimation_in_Average_T_G": 8,
        "First_Estimation_in_Average_T_L": 0,
        "Denoise_Classifier_Free_Guidence_Scale": 1
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Run camenduru/renoise-inversion 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": "camenduru/renoise-inversion:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a",
    "input": {
      "Labmda_AC": 20,
      "Input_Image": "https://replicate.delivery/pbxt/Kc7elOyRLky80eMlw7oKJXrvOfXNa8GF5LXuC9PLneZNH7qi/kitten.jpg",
      "Source_Prompt": "A kitten is sitting in a basket on a branch",
      "Target_Prompt": "a brokkoli is sitting in a basket on a branch",
      "Labmda_Patch_KL": 0.065,
      "Inversion_Strength": 1,
      "Preform_Noise_Correction": true,
      "Number_of_ReNoise_Iterations": 1,
      "Preform_Estimation_Averaging": true,
      "Last_Estimation_in_Average_T_G": 10,
      "Last_Estimation_in_Average_T_L": 5,
      "First_Estimation_in_Average_T_G": 8,
      "First_Estimation_in_Average_T_L": 0,
      "Denoise_Classifier_Free_Guidence_Scale": 1
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2024-03-22T12:03:44.319770Z",
  "created_at": "2024-03-22T12:00:11.801421Z",
  "data_removed": false,
  "error": null,
  "id": "znh2a5lbxpx4ybgyzsgxlozt3u",
  "input": {
    "Labmda_AC": 20,
    "Input_Image": "https://replicate.delivery/pbxt/Kc7elOyRLky80eMlw7oKJXrvOfXNa8GF5LXuC9PLneZNH7qi/kitten.jpg",
    "Source_Prompt": "A kitten is sitting in a basket on a branch",
    "Target_Prompt": "a brokkoli is sitting in a basket on a branch",
    "Labmda_Patch_KL": 0.065,
    "Inversion_Strength": 1,
    "Preform_Noise_Correction": true,
    "Number_of_ReNoise_Iterations": 1,
    "Preform_Estimation_Averaging": true,
    "Last_Estimation_in_Average_T_G": 10,
    "Last_Estimation_in_Average_T_L": 5,
    "First_Estimation_in_Average_T_G": 8,
    "First_Estimation_in_Average_T_L": 0,
    "Denoise_Classifier_Free_Guidence_Scale": 1
  },
  "logs": "Inverting...\n  0%|          | 0/4 [00:00<?, ?it/s]\n 25%|██▌       | 1/4 [00:00<00:02,  1.27it/s]\n 50%|█████     | 2/4 [00:00<00:00,  2.24it/s]\n 75%|███████▌  | 3/4 [00:01<00:00,  3.03it/s]\n100%|██████████| 4/4 [00:01<00:00,  3.64it/s]\n100%|██████████| 4/4 [00:01<00:00,  2.91it/s]\nGenerating...\n  0%|          | 0/4 [00:00<?, ?it/s]\n 50%|█████     | 2/4 [00:00<00:00, 15.79it/s]\n100%|██████████| 4/4 [00:00<00:00, 15.97it/s]\n100%|██████████| 4/4 [00:00<00:00, 15.93it/s]\nPopping cache",
  "metrics": {
    "predict_time": 3.118733,
    "total_time": 212.518349
  },
  "output": "https://replicate.delivery/pbxt/18ORqE4GOrICGVvU6E7DY0b2Xxcq44kfaLEF2f4McwlfskFlA/image.png",
  "started_at": "2024-03-22T12:03:41.201037Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/znh2a5lbxpx4ybgyzsgxlozt3u",
    "cancel": "https://api.replicate.com/v1/predictions/znh2a5lbxpx4ybgyzsgxlozt3u/cancel"
  },
  "version": "bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a"
}

Generated in

3.1 seconds

Tweak it ShareReport

Prediction

camenduru/renoise-inversion:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a

Model

camenduru/renoise-inversion:bcd108aa

emjzkndbc3lmpkuxhpx6q3uhba

Status

Succeeded

Source

Web

Hardware

A40

Total duration

2.1s

Created

about 1 year ago

Input

Labmda_AC: 20
Input_Image
Source_Prompt: A kitten is sitting in a basket on a branch
Target_Prompt: a dog is sitting in a basket on a branch
Labmda_Patch_KL: 0.065
Inversion_Strength: 1
Preform_Noise_Correction
Number_of_ReNoise_Iterations: 1
Preform_Estimation_Averaging
Last_Estimation_in_Average_T_G: 10
Last_Estimation_in_Average_T_L: 5
First_Estimation_in_Average_T_G: 8
First_Estimation_in_Average_T_L: 0
Denoise_Classifier_Free_Guidence_Scale: 1

{
  "Labmda_AC": 20,
  "Input_Image": "https://replicate.delivery/pbxt/Kc7elOyRLky80eMlw7oKJXrvOfXNa8GF5LXuC9PLneZNH7qi/kitten.jpg",
  "Source_Prompt": "A kitten is sitting in a basket on a branch",
  "Target_Prompt": "a dog is sitting in a basket on a branch",
  "Labmda_Patch_KL": 0.065,
  "Inversion_Strength": 1,
  "Preform_Noise_Correction": true,
  "Number_of_ReNoise_Iterations": 1,
  "Preform_Estimation_Averaging": true,
  "Last_Estimation_in_Average_T_G": 10,
  "Last_Estimation_in_Average_T_L": 5,
  "First_Estimation_in_Average_T_G": 8,
  "First_Estimation_in_Average_T_L": 0,
  "Denoise_Classifier_Free_Guidence_Scale": 1
}

Install Replicate’s Node.js client library:

npm install replicate

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 camenduru/renoise-inversion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "camenduru/renoise-inversion:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a",
  {
    input: {
      Labmda_AC: 20,
      Input_Image: "https://replicate.delivery/pbxt/Kc7elOyRLky80eMlw7oKJXrvOfXNa8GF5LXuC9PLneZNH7qi/kitten.jpg",
      Source_Prompt: "A kitten is sitting in a basket on a branch",
      Target_Prompt: "a dog is sitting in a basket on a branch",
      Labmda_Patch_KL: 0.065,
      Inversion_Strength: 1,
      Preform_Noise_Correction: true,
      Number_of_ReNoise_Iterations: 1,
      Preform_Estimation_Averaging: true,
      Last_Estimation_in_Average_T_G: 10,
      Last_Estimation_in_Average_T_L: 5,
      First_Estimation_in_Average_T_G: 8,
      First_Estimation_in_Average_T_L: 0,
      Denoise_Classifier_Free_Guidence_Scale: 1
    }
  }
);

// To access the file URL:
console.log(output.url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", 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

Import the client:

import replicate

Run camenduru/renoise-inversion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "camenduru/renoise-inversion:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a",
    input={
        "Labmda_AC": 20,
        "Input_Image": "https://replicate.delivery/pbxt/Kc7elOyRLky80eMlw7oKJXrvOfXNa8GF5LXuC9PLneZNH7qi/kitten.jpg",
        "Source_Prompt": "A kitten is sitting in a basket on a branch",
        "Target_Prompt": "a dog is sitting in a basket on a branch",
        "Labmda_Patch_KL": 0.065,
        "Inversion_Strength": 1,
        "Preform_Noise_Correction": True,
        "Number_of_ReNoise_Iterations": 1,
        "Preform_Estimation_Averaging": True,
        "Last_Estimation_in_Average_T_G": 10,
        "Last_Estimation_in_Average_T_L": 5,
        "First_Estimation_in_Average_T_G": 8,
        "First_Estimation_in_Average_T_L": 0,
        "Denoise_Classifier_Free_Guidence_Scale": 1
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Run camenduru/renoise-inversion 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": "camenduru/renoise-inversion:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a",
    "input": {
      "Labmda_AC": 20,
      "Input_Image": "https://replicate.delivery/pbxt/Kc7elOyRLky80eMlw7oKJXrvOfXNa8GF5LXuC9PLneZNH7qi/kitten.jpg",
      "Source_Prompt": "A kitten is sitting in a basket on a branch",
      "Target_Prompt": "a dog is sitting in a basket on a branch",
      "Labmda_Patch_KL": 0.065,
      "Inversion_Strength": 1,
      "Preform_Noise_Correction": true,
      "Number_of_ReNoise_Iterations": 1,
      "Preform_Estimation_Averaging": true,
      "Last_Estimation_in_Average_T_G": 10,
      "Last_Estimation_in_Average_T_L": 5,
      "First_Estimation_in_Average_T_G": 8,
      "First_Estimation_in_Average_T_L": 0,
      "Denoise_Classifier_Free_Guidence_Scale": 1
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2024-03-22T12:04:24.776421Z",
  "created_at": "2024-03-22T12:04:22.648575Z",
  "data_removed": false,
  "error": null,
  "id": "emjzkndbc3lmpkuxhpx6q3uhba",
  "input": {
    "Labmda_AC": 20,
    "Input_Image": "https://replicate.delivery/pbxt/Kc7elOyRLky80eMlw7oKJXrvOfXNa8GF5LXuC9PLneZNH7qi/kitten.jpg",
    "Source_Prompt": "A kitten is sitting in a basket on a branch",
    "Target_Prompt": "a dog is sitting in a basket on a branch",
    "Labmda_Patch_KL": 0.065,
    "Inversion_Strength": 1,
    "Preform_Noise_Correction": true,
    "Number_of_ReNoise_Iterations": 1,
    "Preform_Estimation_Averaging": true,
    "Last_Estimation_in_Average_T_G": 10,
    "Last_Estimation_in_Average_T_L": 5,
    "First_Estimation_in_Average_T_G": 8,
    "First_Estimation_in_Average_T_L": 0,
    "Denoise_Classifier_Free_Guidence_Scale": 1
  },
  "logs": "Inverting...\n  0%|          | 0/4 [00:00<?, ?it/s]\n 25%|██▌       | 1/4 [00:00<00:01,  2.04it/s]\n 50%|█████     | 2/4 [00:00<00:00,  3.16it/s]\n 75%|███████▌  | 3/4 [00:00<00:00,  3.79it/s]\n100%|██████████| 4/4 [00:01<00:00,  4.24it/s]\n100%|██████████| 4/4 [00:01<00:00,  3.71it/s]\nGenerating...\n  0%|          | 0/4 [00:00<?, ?it/s]\n 50%|█████     | 2/4 [00:00<00:00, 15.14it/s]\n100%|██████████| 4/4 [00:00<00:00, 15.33it/s]\n100%|██████████| 4/4 [00:00<00:00, 15.30it/s]\nPopping cache",
  "metrics": {
    "predict_time": 2.117347,
    "total_time": 2.127846
  },
  "output": "https://replicate.delivery/pbxt/cjyxNmqd0WLeESb87DNepH5PapgfbfiBHIIkyOnJJ5xicJLKB/image.png",
  "started_at": "2024-03-22T12:04:22.659074Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/emjzkndbc3lmpkuxhpx6q3uhba",
    "cancel": "https://api.replicate.com/v1/predictions/emjzkndbc3lmpkuxhpx6q3uhba/cancel"
  },
  "version": "bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a"
}

Generated in

2.1 seconds

Tweak it ShareReport

Prediction

camenduru/renoise-inversion:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a

Model

camenduru/renoise-inversion:bcd108aa

lq4rdcdb2o3k53x2o7nigb74eu

Status

Succeeded

Source

Web

Hardware

A40

Total duration

4m 27s

Created

about 1 year ago

Input

Labmda_AC: 20
Input_Image
Source_Prompt: A kitten is sitting in a basket on a branch
Target_Prompt: a lego kitten is sitting in a basket on a branch
Labmda_Patch_KL: 0.065
Inversion_Strength: 1
Preform_Noise_Correction
Number_of_ReNoise_Iterations: 9
Preform_Estimation_Averaging
Last_Estimation_in_Average_T_G: 10
Last_Estimation_in_Average_T_L: 5
First_Estimation_in_Average_T_G: 8
First_Estimation_in_Average_T_L: 0
Denoise_Classifier_Free_Guidence_Scale: 1

{
  "Labmda_AC": 20,
  "Input_Image": "https://replicate.delivery/pbxt/Kc7elOyRLky80eMlw7oKJXrvOfXNa8GF5LXuC9PLneZNH7qi/kitten.jpg",
  "Source_Prompt": "A kitten is sitting in a basket on a branch",
  "Target_Prompt": "a lego kitten is sitting in a basket on a branch",
  "Labmda_Patch_KL": 0.065,
  "Inversion_Strength": 1,
  "Preform_Noise_Correction": true,
  "Number_of_ReNoise_Iterations": 9,
  "Preform_Estimation_Averaging": true,
  "Last_Estimation_in_Average_T_G": 10,
  "Last_Estimation_in_Average_T_L": 5,
  "First_Estimation_in_Average_T_G": 8,
  "First_Estimation_in_Average_T_L": 0,
  "Denoise_Classifier_Free_Guidence_Scale": 1
}

Install Replicate’s Node.js client library:

npm install replicate

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 camenduru/renoise-inversion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "camenduru/renoise-inversion:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a",
  {
    input: {
      Labmda_AC: 20,
      Input_Image: "https://replicate.delivery/pbxt/Kc7elOyRLky80eMlw7oKJXrvOfXNa8GF5LXuC9PLneZNH7qi/kitten.jpg",
      Source_Prompt: "A kitten is sitting in a basket on a branch",
      Target_Prompt: "a lego kitten is sitting in a basket on a branch",
      Labmda_Patch_KL: 0.065,
      Inversion_Strength: 1,
      Preform_Noise_Correction: true,
      Number_of_ReNoise_Iterations: 9,
      Preform_Estimation_Averaging: true,
      Last_Estimation_in_Average_T_G: 10,
      Last_Estimation_in_Average_T_L: 5,
      First_Estimation_in_Average_T_G: 8,
      First_Estimation_in_Average_T_L: 0,
      Denoise_Classifier_Free_Guidence_Scale: 1
    }
  }
);

// To access the file URL:
console.log(output.url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", 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

Import the client:

import replicate

Run camenduru/renoise-inversion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "camenduru/renoise-inversion:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a",
    input={
        "Labmda_AC": 20,
        "Input_Image": "https://replicate.delivery/pbxt/Kc7elOyRLky80eMlw7oKJXrvOfXNa8GF5LXuC9PLneZNH7qi/kitten.jpg",
        "Source_Prompt": "A kitten is sitting in a basket on a branch",
        "Target_Prompt": "a lego kitten is sitting in a basket on a branch",
        "Labmda_Patch_KL": 0.065,
        "Inversion_Strength": 1,
        "Preform_Noise_Correction": True,
        "Number_of_ReNoise_Iterations": 9,
        "Preform_Estimation_Averaging": True,
        "Last_Estimation_in_Average_T_G": 10,
        "Last_Estimation_in_Average_T_L": 5,
        "First_Estimation_in_Average_T_G": 8,
        "First_Estimation_in_Average_T_L": 0,
        "Denoise_Classifier_Free_Guidence_Scale": 1
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Run camenduru/renoise-inversion 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": "camenduru/renoise-inversion:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a",
    "input": {
      "Labmda_AC": 20,
      "Input_Image": "https://replicate.delivery/pbxt/Kc7elOyRLky80eMlw7oKJXrvOfXNa8GF5LXuC9PLneZNH7qi/kitten.jpg",
      "Source_Prompt": "A kitten is sitting in a basket on a branch",
      "Target_Prompt": "a lego kitten is sitting in a basket on a branch",
      "Labmda_Patch_KL": 0.065,
      "Inversion_Strength": 1,
      "Preform_Noise_Correction": true,
      "Number_of_ReNoise_Iterations": 9,
      "Preform_Estimation_Averaging": true,
      "Last_Estimation_in_Average_T_G": 10,
      "Last_Estimation_in_Average_T_L": 5,
      "First_Estimation_in_Average_T_G": 8,
      "First_Estimation_in_Average_T_L": 0,
      "Denoise_Classifier_Free_Guidence_Scale": 1
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2024-03-22T12:13:52.837529Z",
  "created_at": "2024-03-22T12:09:25.614702Z",
  "data_removed": false,
  "error": null,
  "id": "lq4rdcdb2o3k53x2o7nigb74eu",
  "input": {
    "Labmda_AC": 20,
    "Input_Image": "https://replicate.delivery/pbxt/Kc7elOyRLky80eMlw7oKJXrvOfXNa8GF5LXuC9PLneZNH7qi/kitten.jpg",
    "Source_Prompt": "A kitten is sitting in a basket on a branch",
    "Target_Prompt": "a lego kitten is sitting in a basket on a branch",
    "Labmda_Patch_KL": 0.065,
    "Inversion_Strength": 1,
    "Preform_Noise_Correction": true,
    "Number_of_ReNoise_Iterations": 9,
    "Preform_Estimation_Averaging": true,
    "Last_Estimation_in_Average_T_G": 10,
    "Last_Estimation_in_Average_T_L": 5,
    "First_Estimation_in_Average_T_G": 8,
    "First_Estimation_in_Average_T_L": 0,
    "Denoise_Classifier_Free_Guidence_Scale": 1
  },
  "logs": "Inverting...\n  0%|          | 0/4 [00:00<?, ?it/s]\n 25%|██▌       | 1/4 [00:01<00:05,  1.69s/it]\n 50%|█████     | 2/4 [00:02<00:02,  1.32s/it]\n 75%|███████▌  | 3/4 [00:03<00:01,  1.22s/it]\n100%|██████████| 4/4 [00:04<00:00,  1.16s/it]\n100%|██████████| 4/4 [00:04<00:00,  1.23s/it]\nGenerating...\n  0%|          | 0/4 [00:00<?, ?it/s]\n 50%|█████     | 2/4 [00:00<00:00, 14.56it/s]\n100%|██████████| 4/4 [00:00<00:00, 14.35it/s]\n100%|██████████| 4/4 [00:00<00:00, 14.37it/s]\nPopping cache",
  "metrics": {
    "predict_time": 8.021843,
    "total_time": 267.222827
  },
  "output": "https://replicate.delivery/pbxt/vUeIc1hHfpuLX0zsPwKRKWMX7NiJ0pJGUej4L5jBBhpefTWUC/image.png",
  "started_at": "2024-03-22T12:13:44.815686Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/lq4rdcdb2o3k53x2o7nigb74eu",
    "cancel": "https://api.replicate.com/v1/predictions/lq4rdcdb2o3k53x2o7nigb74eu/cancel"
  },
  "version": "bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a"
}

Generated in

8.0 seconds

Tweak it ShareReport

Prediction

camenduru/renoise-inversion:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a

Model

camenduru/renoise-inversion:bcd108aa

kp4dirlb2vf23ddzcxsvn6rugy

Status

Succeeded

Source

Web

Hardware

A40

Total duration

5.5s

Created

about 1 year ago

Input

Labmda_AC: 20
Input_Image
Source_Prompt: A kitten is sitting in a basket on a branch
Target_Prompt: a dog is sitting in a basket on a branch
Labmda_Patch_KL: 0.065
Inversion_Strength: 1
Preform_Noise_Correction
Number_of_ReNoise_Iterations: 7
Preform_Estimation_Averaging
Last_Estimation_in_Average_T_G: 10
Last_Estimation_in_Average_T_L: 5
First_Estimation_in_Average_T_G: 8
First_Estimation_in_Average_T_L: 0
Denoise_Classifier_Free_Guidence_Scale: 1

{
  "Labmda_AC": 20,
  "Input_Image": "https://replicate.delivery/pbxt/Kc7elOyRLky80eMlw7oKJXrvOfXNa8GF5LXuC9PLneZNH7qi/kitten.jpg",
  "Source_Prompt": "A kitten is sitting in a basket on a branch",
  "Target_Prompt": "a dog is sitting in a basket on a branch",
  "Labmda_Patch_KL": 0.065,
  "Inversion_Strength": 1,
  "Preform_Noise_Correction": true,
  "Number_of_ReNoise_Iterations": 7,
  "Preform_Estimation_Averaging": true,
  "Last_Estimation_in_Average_T_G": 10,
  "Last_Estimation_in_Average_T_L": 5,
  "First_Estimation_in_Average_T_G": 8,
  "First_Estimation_in_Average_T_L": 0,
  "Denoise_Classifier_Free_Guidence_Scale": 1
}

Install Replicate’s Node.js client library:

npm install replicate

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 camenduru/renoise-inversion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "camenduru/renoise-inversion:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a",
  {
    input: {
      Labmda_AC: 20,
      Input_Image: "https://replicate.delivery/pbxt/Kc7elOyRLky80eMlw7oKJXrvOfXNa8GF5LXuC9PLneZNH7qi/kitten.jpg",
      Source_Prompt: "A kitten is sitting in a basket on a branch",
      Target_Prompt: "a dog is sitting in a basket on a branch",
      Labmda_Patch_KL: 0.065,
      Inversion_Strength: 1,
      Preform_Noise_Correction: true,
      Number_of_ReNoise_Iterations: 7,
      Preform_Estimation_Averaging: true,
      Last_Estimation_in_Average_T_G: 10,
      Last_Estimation_in_Average_T_L: 5,
      First_Estimation_in_Average_T_G: 8,
      First_Estimation_in_Average_T_L: 0,
      Denoise_Classifier_Free_Guidence_Scale: 1
    }
  }
);

// To access the file URL:
console.log(output.url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", 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

Import the client:

import replicate

Run camenduru/renoise-inversion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "camenduru/renoise-inversion:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a",
    input={
        "Labmda_AC": 20,
        "Input_Image": "https://replicate.delivery/pbxt/Kc7elOyRLky80eMlw7oKJXrvOfXNa8GF5LXuC9PLneZNH7qi/kitten.jpg",
        "Source_Prompt": "A kitten is sitting in a basket on a branch",
        "Target_Prompt": "a dog is sitting in a basket on a branch",
        "Labmda_Patch_KL": 0.065,
        "Inversion_Strength": 1,
        "Preform_Noise_Correction": True,
        "Number_of_ReNoise_Iterations": 7,
        "Preform_Estimation_Averaging": True,
        "Last_Estimation_in_Average_T_G": 10,
        "Last_Estimation_in_Average_T_L": 5,
        "First_Estimation_in_Average_T_G": 8,
        "First_Estimation_in_Average_T_L": 0,
        "Denoise_Classifier_Free_Guidence_Scale": 1
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Run camenduru/renoise-inversion 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": "camenduru/renoise-inversion:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a",
    "input": {
      "Labmda_AC": 20,
      "Input_Image": "https://replicate.delivery/pbxt/Kc7elOyRLky80eMlw7oKJXrvOfXNa8GF5LXuC9PLneZNH7qi/kitten.jpg",
      "Source_Prompt": "A kitten is sitting in a basket on a branch",
      "Target_Prompt": "a dog is sitting in a basket on a branch",
      "Labmda_Patch_KL": 0.065,
      "Inversion_Strength": 1,
      "Preform_Noise_Correction": true,
      "Number_of_ReNoise_Iterations": 7,
      "Preform_Estimation_Averaging": true,
      "Last_Estimation_in_Average_T_G": 10,
      "Last_Estimation_in_Average_T_L": 5,
      "First_Estimation_in_Average_T_G": 8,
      "First_Estimation_in_Average_T_L": 0,
      "Denoise_Classifier_Free_Guidence_Scale": 1
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2024-03-22T12:15:57.727305Z",
  "created_at": "2024-03-22T12:15:52.214493Z",
  "data_removed": false,
  "error": null,
  "id": "kp4dirlb2vf23ddzcxsvn6rugy",
  "input": {
    "Labmda_AC": 20,
    "Input_Image": "https://replicate.delivery/pbxt/Kc7elOyRLky80eMlw7oKJXrvOfXNa8GF5LXuC9PLneZNH7qi/kitten.jpg",
    "Source_Prompt": "A kitten is sitting in a basket on a branch",
    "Target_Prompt": "a dog is sitting in a basket on a branch",
    "Labmda_Patch_KL": 0.065,
    "Inversion_Strength": 1,
    "Preform_Noise_Correction": true,
    "Number_of_ReNoise_Iterations": 7,
    "Preform_Estimation_Averaging": true,
    "Last_Estimation_in_Average_T_G": 10,
    "Last_Estimation_in_Average_T_L": 5,
    "First_Estimation_in_Average_T_G": 8,
    "First_Estimation_in_Average_T_L": 0,
    "Denoise_Classifier_Free_Guidence_Scale": 1
  },
  "logs": "Inverting...\n  0%|          | 0/4 [00:00<?, ?it/s]\n 25%|██▌       | 1/4 [00:01<00:04,  1.39s/it]\n 50%|█████     | 2/4 [00:02<00:01,  1.06it/s]\n 75%|███████▌  | 3/4 [00:02<00:00,  1.25it/s]\n100%|██████████| 4/4 [00:03<00:00,  1.38it/s]\n100%|██████████| 4/4 [00:03<00:00,  1.23it/s]\nGenerating...\n  0%|          | 0/4 [00:00<?, ?it/s]\n 50%|█████     | 2/4 [00:00<00:00, 14.44it/s]\n100%|██████████| 4/4 [00:00<00:00, 14.03it/s]\n100%|██████████| 4/4 [00:00<00:00, 14.08it/s]\nPopping cache",
  "metrics": {
    "predict_time": 5.470123,
    "total_time": 5.512812
  },
  "output": "https://replicate.delivery/pbxt/bKWopi2L3O71KVBF31Ja4bfpMAKP89sDnO5iNafq4CM8hyiSA/image.png",
  "started_at": "2024-03-22T12:15:52.257182Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/kp4dirlb2vf23ddzcxsvn6rugy",
    "cancel": "https://api.replicate.com/v1/predictions/kp4dirlb2vf23ddzcxsvn6rugy/cancel"
  },
  "version": "bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a"
}

Generated in

5.5 seconds

Tweak it ShareReport

Prediction

camenduru/renoise-inversion:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a

Model

camenduru/renoise-inversion:bcd108aa

yvobrsdb43deife5rpx6xfjbm4

Status

Succeeded

Source

Web

Hardware

A40

Total duration

7.2s

Created

about 1 year ago

Input

Labmda_AC: 20
Input_Image
Source_Prompt: a lion is sitting in the grass at sunset
Target_Prompt: a tiger is sitting in the grass at sunset
Labmda_Patch_KL: 0.065
Inversion_Strength: 1
Preform_Noise_Correction
Number_of_ReNoise_Iterations: 9
Preform_Estimation_Averaging
Last_Estimation_in_Average_T_G: 10
Last_Estimation_in_Average_T_L: 5
First_Estimation_in_Average_T_G: 8
First_Estimation_in_Average_T_L: 0
Denoise_Classifier_Free_Guidence_Scale: 1

{
  "Labmda_AC": 20,
  "Input_Image": "https://replicate.delivery/pbxt/Kc7rZoVxahwLtPT4ukxIuYPfUNjiLS5x1JGpcZtGoQvqojcW/lion.jpg",
  "Source_Prompt": "a lion is sitting in the grass at sunset",
  "Target_Prompt": "a tiger is sitting in the grass at sunset",
  "Labmda_Patch_KL": 0.065,
  "Inversion_Strength": 1,
  "Preform_Noise_Correction": true,
  "Number_of_ReNoise_Iterations": 9,
  "Preform_Estimation_Averaging": true,
  "Last_Estimation_in_Average_T_G": 10,
  "Last_Estimation_in_Average_T_L": 5,
  "First_Estimation_in_Average_T_G": 8,
  "First_Estimation_in_Average_T_L": 0,
  "Denoise_Classifier_Free_Guidence_Scale": 1
}

Install Replicate’s Node.js client library:

npm install replicate

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 camenduru/renoise-inversion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "camenduru/renoise-inversion:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a",
  {
    input: {
      Labmda_AC: 20,
      Input_Image: "https://replicate.delivery/pbxt/Kc7rZoVxahwLtPT4ukxIuYPfUNjiLS5x1JGpcZtGoQvqojcW/lion.jpg",
      Source_Prompt: "a lion is sitting in the grass at sunset",
      Target_Prompt: "a tiger is sitting in the grass at sunset",
      Labmda_Patch_KL: 0.065,
      Inversion_Strength: 1,
      Preform_Noise_Correction: true,
      Number_of_ReNoise_Iterations: 9,
      Preform_Estimation_Averaging: true,
      Last_Estimation_in_Average_T_G: 10,
      Last_Estimation_in_Average_T_L: 5,
      First_Estimation_in_Average_T_G: 8,
      First_Estimation_in_Average_T_L: 0,
      Denoise_Classifier_Free_Guidence_Scale: 1
    }
  }
);

// To access the file URL:
console.log(output.url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", 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

Import the client:

import replicate

Run camenduru/renoise-inversion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "camenduru/renoise-inversion:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a",
    input={
        "Labmda_AC": 20,
        "Input_Image": "https://replicate.delivery/pbxt/Kc7rZoVxahwLtPT4ukxIuYPfUNjiLS5x1JGpcZtGoQvqojcW/lion.jpg",
        "Source_Prompt": "a lion is sitting in the grass at sunset",
        "Target_Prompt": "a tiger is sitting in the grass at sunset",
        "Labmda_Patch_KL": 0.065,
        "Inversion_Strength": 1,
        "Preform_Noise_Correction": True,
        "Number_of_ReNoise_Iterations": 9,
        "Preform_Estimation_Averaging": True,
        "Last_Estimation_in_Average_T_G": 10,
        "Last_Estimation_in_Average_T_L": 5,
        "First_Estimation_in_Average_T_G": 8,
        "First_Estimation_in_Average_T_L": 0,
        "Denoise_Classifier_Free_Guidence_Scale": 1
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Run camenduru/renoise-inversion 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": "camenduru/renoise-inversion:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a",
    "input": {
      "Labmda_AC": 20,
      "Input_Image": "https://replicate.delivery/pbxt/Kc7rZoVxahwLtPT4ukxIuYPfUNjiLS5x1JGpcZtGoQvqojcW/lion.jpg",
      "Source_Prompt": "a lion is sitting in the grass at sunset",
      "Target_Prompt": "a tiger is sitting in the grass at sunset",
      "Labmda_Patch_KL": 0.065,
      "Inversion_Strength": 1,
      "Preform_Noise_Correction": true,
      "Number_of_ReNoise_Iterations": 9,
      "Preform_Estimation_Averaging": true,
      "Last_Estimation_in_Average_T_G": 10,
      "Last_Estimation_in_Average_T_L": 5,
      "First_Estimation_in_Average_T_G": 8,
      "First_Estimation_in_Average_T_L": 0,
      "Denoise_Classifier_Free_Guidence_Scale": 1
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2024-03-22T12:17:24.467131Z",
  "created_at": "2024-03-22T12:17:17.325899Z",
  "data_removed": false,
  "error": null,
  "id": "yvobrsdb43deife5rpx6xfjbm4",
  "input": {
    "Labmda_AC": 20,
    "Input_Image": "https://replicate.delivery/pbxt/Kc7rZoVxahwLtPT4ukxIuYPfUNjiLS5x1JGpcZtGoQvqojcW/lion.jpg",
    "Source_Prompt": "a lion is sitting in the grass at sunset",
    "Target_Prompt": "a tiger is sitting in the grass at sunset",
    "Labmda_Patch_KL": 0.065,
    "Inversion_Strength": 1,
    "Preform_Noise_Correction": true,
    "Number_of_ReNoise_Iterations": 9,
    "Preform_Estimation_Averaging": true,
    "Last_Estimation_in_Average_T_G": 10,
    "Last_Estimation_in_Average_T_L": 5,
    "First_Estimation_in_Average_T_G": 8,
    "First_Estimation_in_Average_T_L": 0,
    "Denoise_Classifier_Free_Guidence_Scale": 1
  },
  "logs": "Inverting...\n  0%|          | 0/4 [00:00<?, ?it/s]\n 25%|██▌       | 1/4 [00:01<00:04,  1.38s/it]\n 50%|█████     | 2/4 [00:02<00:02,  1.21s/it]\n 75%|███████▌  | 3/4 [00:03<00:01,  1.14s/it]\n100%|██████████| 4/4 [00:04<00:00,  1.11s/it]\n100%|██████████| 4/4 [00:04<00:00,  1.15s/it]\nGenerating...\n  0%|          | 0/4 [00:00<?, ?it/s]\n 50%|█████     | 2/4 [00:00<00:00, 15.40it/s]\n100%|██████████| 4/4 [00:00<00:00, 15.75it/s]\n100%|██████████| 4/4 [00:00<00:00, 15.69it/s]\nPopping cache",
  "metrics": {
    "predict_time": 7.097825,
    "total_time": 7.141232
  },
  "output": "https://replicate.delivery/pbxt/vTqw4nfA6UV0GqLpWvX8BAoQPoOFQsW3qxkOJm25JgypRZRJA/image.png",
  "started_at": "2024-03-22T12:17:17.369306Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/yvobrsdb43deife5rpx6xfjbm4",
    "cancel": "https://api.replicate.com/v1/predictions/yvobrsdb43deife5rpx6xfjbm4/cancel"
  },
  "version": "bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a"
}

Generated in

7.1 seconds

Tweak it ShareReport

Prediction

camenduru/renoise-inversion:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a

Model

camenduru/renoise-inversion:bcd108aa

o7hxittbfvyhdttc5xaz44yqfq

Status

Succeeded

Source

Web

Hardware

A40

Total duration

7.2s

Created

about 1 year ago

Input

Labmda_AC: 20
Input_Image
Source_Prompt: a monkey sitting on a tree branch in the forest
Target_Prompt: a beaver sitting on a tree branch in the forest
Labmda_Patch_KL: 0.065
Inversion_Strength: 1
Preform_Noise_Correction
Number_of_ReNoise_Iterations: 9
Preform_Estimation_Averaging
Last_Estimation_in_Average_T_G: 10
Last_Estimation_in_Average_T_L: 5
First_Estimation_in_Average_T_G: 8
First_Estimation_in_Average_T_L: 0
Denoise_Classifier_Free_Guidence_Scale: 1

{
  "Labmda_AC": 20,
  "Input_Image": "https://replicate.delivery/pbxt/Kc7qyNxBsLB3XOlKx9BchF1whU0d9zPXR9XJsrp1BMNaCt7g/monkey.jpg",
  "Source_Prompt": "a monkey sitting on a tree branch in the forest",
  "Target_Prompt": "a beaver sitting on a tree branch in the forest",
  "Labmda_Patch_KL": 0.065,
  "Inversion_Strength": 1,
  "Preform_Noise_Correction": true,
  "Number_of_ReNoise_Iterations": 9,
  "Preform_Estimation_Averaging": true,
  "Last_Estimation_in_Average_T_G": 10,
  "Last_Estimation_in_Average_T_L": 5,
  "First_Estimation_in_Average_T_G": 8,
  "First_Estimation_in_Average_T_L": 0,
  "Denoise_Classifier_Free_Guidence_Scale": 1
}

Install Replicate’s Node.js client library:

npm install replicate

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 camenduru/renoise-inversion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "camenduru/renoise-inversion:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a",
  {
    input: {
      Labmda_AC: 20,
      Input_Image: "https://replicate.delivery/pbxt/Kc7qyNxBsLB3XOlKx9BchF1whU0d9zPXR9XJsrp1BMNaCt7g/monkey.jpg",
      Source_Prompt: "a monkey sitting on a tree branch in the forest",
      Target_Prompt: "a beaver sitting on a tree branch in the forest",
      Labmda_Patch_KL: 0.065,
      Inversion_Strength: 1,
      Preform_Noise_Correction: true,
      Number_of_ReNoise_Iterations: 9,
      Preform_Estimation_Averaging: true,
      Last_Estimation_in_Average_T_G: 10,
      Last_Estimation_in_Average_T_L: 5,
      First_Estimation_in_Average_T_G: 8,
      First_Estimation_in_Average_T_L: 0,
      Denoise_Classifier_Free_Guidence_Scale: 1
    }
  }
);

// To access the file URL:
console.log(output.url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", 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

Import the client:

import replicate

Run camenduru/renoise-inversion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "camenduru/renoise-inversion:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a",
    input={
        "Labmda_AC": 20,
        "Input_Image": "https://replicate.delivery/pbxt/Kc7qyNxBsLB3XOlKx9BchF1whU0d9zPXR9XJsrp1BMNaCt7g/monkey.jpg",
        "Source_Prompt": "a monkey sitting on a tree branch in the forest",
        "Target_Prompt": "a beaver sitting on a tree branch in the forest",
        "Labmda_Patch_KL": 0.065,
        "Inversion_Strength": 1,
        "Preform_Noise_Correction": True,
        "Number_of_ReNoise_Iterations": 9,
        "Preform_Estimation_Averaging": True,
        "Last_Estimation_in_Average_T_G": 10,
        "Last_Estimation_in_Average_T_L": 5,
        "First_Estimation_in_Average_T_G": 8,
        "First_Estimation_in_Average_T_L": 0,
        "Denoise_Classifier_Free_Guidence_Scale": 1
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Run camenduru/renoise-inversion 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": "camenduru/renoise-inversion:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a",
    "input": {
      "Labmda_AC": 20,
      "Input_Image": "https://replicate.delivery/pbxt/Kc7qyNxBsLB3XOlKx9BchF1whU0d9zPXR9XJsrp1BMNaCt7g/monkey.jpg",
      "Source_Prompt": "a monkey sitting on a tree branch in the forest",
      "Target_Prompt": "a beaver sitting on a tree branch in the forest",
      "Labmda_Patch_KL": 0.065,
      "Inversion_Strength": 1,
      "Preform_Noise_Correction": true,
      "Number_of_ReNoise_Iterations": 9,
      "Preform_Estimation_Averaging": true,
      "Last_Estimation_in_Average_T_G": 10,
      "Last_Estimation_in_Average_T_L": 5,
      "First_Estimation_in_Average_T_G": 8,
      "First_Estimation_in_Average_T_L": 0,
      "Denoise_Classifier_Free_Guidence_Scale": 1
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2024-03-22T12:16:39.616387Z",
  "created_at": "2024-03-22T12:16:32.445451Z",
  "data_removed": false,
  "error": null,
  "id": "o7hxittbfvyhdttc5xaz44yqfq",
  "input": {
    "Labmda_AC": 20,
    "Input_Image": "https://replicate.delivery/pbxt/Kc7qyNxBsLB3XOlKx9BchF1whU0d9zPXR9XJsrp1BMNaCt7g/monkey.jpg",
    "Source_Prompt": "a monkey sitting on a tree branch in the forest",
    "Target_Prompt": "a beaver sitting on a tree branch in the forest",
    "Labmda_Patch_KL": 0.065,
    "Inversion_Strength": 1,
    "Preform_Noise_Correction": true,
    "Number_of_ReNoise_Iterations": 9,
    "Preform_Estimation_Averaging": true,
    "Last_Estimation_in_Average_T_G": 10,
    "Last_Estimation_in_Average_T_L": 5,
    "First_Estimation_in_Average_T_G": 8,
    "First_Estimation_in_Average_T_L": 0,
    "Denoise_Classifier_Free_Guidence_Scale": 1
  },
  "logs": "Inverting...\n  0%|          | 0/4 [00:00<?, ?it/s]\n 25%|██▌       | 1/4 [00:01<00:04,  1.39s/it]\n 50%|█████     | 2/4 [00:02<00:02,  1.21s/it]\n 75%|███████▌  | 3/4 [00:03<00:01,  1.14s/it]\n100%|██████████| 4/4 [00:04<00:00,  1.11s/it]\n100%|██████████| 4/4 [00:04<00:00,  1.15s/it]\nGenerating...\n  0%|          | 0/4 [00:00<?, ?it/s]\n 50%|█████     | 2/4 [00:00<00:00, 14.37it/s]\n100%|██████████| 4/4 [00:00<00:00, 14.44it/s]\n100%|██████████| 4/4 [00:00<00:00, 14.42it/s]\nPopping cache",
  "metrics": {
    "predict_time": 7.127554,
    "total_time": 7.170936
  },
  "output": "https://replicate.delivery/pbxt/QppDpJtm7e2bR6DoAwGHnTcideWN59aIg3IOWlwpeNWNFlFlA/image.png",
  "started_at": "2024-03-22T12:16:32.488833Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/o7hxittbfvyhdttc5xaz44yqfq",
    "cancel": "https://api.replicate.com/v1/predictions/o7hxittbfvyhdttc5xaz44yqfq/cancel"
  },
  "version": "bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a"
}

Generated in

7.1 seconds

Tweak it ShareReport

Prediction

camenduru/renoise-inversion:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a

Model

camenduru/renoise-inversion:bcd108aa

6top3ftbacev7tfft7yk4no4za

Status

Succeeded

Source

Web

Hardware

A40

Total duration

2.4s

Created

about 1 year ago

Input

Labmda_AC: 20
Input_Image
Source_Prompt: a lion is sitting in the grass at sunset
Target_Prompt: a tiger is sitting in the grass at sunset
Labmda_Patch_KL: 0.065
Inversion_Strength: 1
Preform_Noise_Correction
Number_of_ReNoise_Iterations: 1
Preform_Estimation_Averaging
Last_Estimation_in_Average_T_G: 10
Last_Estimation_in_Average_T_L: 5
First_Estimation_in_Average_T_G: 8
First_Estimation_in_Average_T_L: 0
Denoise_Classifier_Free_Guidence_Scale: 1

{
  "Labmda_AC": 20,
  "Input_Image": "https://replicate.delivery/pbxt/Kc7rZoVxahwLtPT4ukxIuYPfUNjiLS5x1JGpcZtGoQvqojcW/lion.jpg",
  "Source_Prompt": "a lion is sitting in the grass at sunset",
  "Target_Prompt": "a tiger is sitting in the grass at sunset",
  "Labmda_Patch_KL": 0.065,
  "Inversion_Strength": 1,
  "Preform_Noise_Correction": true,
  "Number_of_ReNoise_Iterations": 1,
  "Preform_Estimation_Averaging": true,
  "Last_Estimation_in_Average_T_G": 10,
  "Last_Estimation_in_Average_T_L": 5,
  "First_Estimation_in_Average_T_G": 8,
  "First_Estimation_in_Average_T_L": 0,
  "Denoise_Classifier_Free_Guidence_Scale": 1
}

Install Replicate’s Node.js client library:

npm install replicate

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 camenduru/renoise-inversion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "camenduru/renoise-inversion:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a",
  {
    input: {
      Labmda_AC: 20,
      Input_Image: "https://replicate.delivery/pbxt/Kc7rZoVxahwLtPT4ukxIuYPfUNjiLS5x1JGpcZtGoQvqojcW/lion.jpg",
      Source_Prompt: "a lion is sitting in the grass at sunset",
      Target_Prompt: "a tiger is sitting in the grass at sunset",
      Labmda_Patch_KL: 0.065,
      Inversion_Strength: 1,
      Preform_Noise_Correction: true,
      Number_of_ReNoise_Iterations: 1,
      Preform_Estimation_Averaging: true,
      Last_Estimation_in_Average_T_G: 10,
      Last_Estimation_in_Average_T_L: 5,
      First_Estimation_in_Average_T_G: 8,
      First_Estimation_in_Average_T_L: 0,
      Denoise_Classifier_Free_Guidence_Scale: 1
    }
  }
);

// To access the file URL:
console.log(output.url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", 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

Import the client:

import replicate

Run camenduru/renoise-inversion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "camenduru/renoise-inversion:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a",
    input={
        "Labmda_AC": 20,
        "Input_Image": "https://replicate.delivery/pbxt/Kc7rZoVxahwLtPT4ukxIuYPfUNjiLS5x1JGpcZtGoQvqojcW/lion.jpg",
        "Source_Prompt": "a lion is sitting in the grass at sunset",
        "Target_Prompt": "a tiger is sitting in the grass at sunset",
        "Labmda_Patch_KL": 0.065,
        "Inversion_Strength": 1,
        "Preform_Noise_Correction": True,
        "Number_of_ReNoise_Iterations": 1,
        "Preform_Estimation_Averaging": True,
        "Last_Estimation_in_Average_T_G": 10,
        "Last_Estimation_in_Average_T_L": 5,
        "First_Estimation_in_Average_T_G": 8,
        "First_Estimation_in_Average_T_L": 0,
        "Denoise_Classifier_Free_Guidence_Scale": 1
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Run camenduru/renoise-inversion 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": "camenduru/renoise-inversion:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a",
    "input": {
      "Labmda_AC": 20,
      "Input_Image": "https://replicate.delivery/pbxt/Kc7rZoVxahwLtPT4ukxIuYPfUNjiLS5x1JGpcZtGoQvqojcW/lion.jpg",
      "Source_Prompt": "a lion is sitting in the grass at sunset",
      "Target_Prompt": "a tiger is sitting in the grass at sunset",
      "Labmda_Patch_KL": 0.065,
      "Inversion_Strength": 1,
      "Preform_Noise_Correction": true,
      "Number_of_ReNoise_Iterations": 1,
      "Preform_Estimation_Averaging": true,
      "Last_Estimation_in_Average_T_G": 10,
      "Last_Estimation_in_Average_T_L": 5,
      "First_Estimation_in_Average_T_G": 8,
      "First_Estimation_in_Average_T_L": 0,
      "Denoise_Classifier_Free_Guidence_Scale": 1
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2024-03-22T12:05:52.085820Z",
  "created_at": "2024-03-22T12:05:49.704437Z",
  "data_removed": false,
  "error": null,
  "id": "6top3ftbacev7tfft7yk4no4za",
  "input": {
    "Labmda_AC": 20,
    "Input_Image": "https://replicate.delivery/pbxt/Kc7rZoVxahwLtPT4ukxIuYPfUNjiLS5x1JGpcZtGoQvqojcW/lion.jpg",
    "Source_Prompt": "a lion is sitting in the grass at sunset",
    "Target_Prompt": "a tiger is sitting in the grass at sunset",
    "Labmda_Patch_KL": 0.065,
    "Inversion_Strength": 1,
    "Preform_Noise_Correction": true,
    "Number_of_ReNoise_Iterations": 1,
    "Preform_Estimation_Averaging": true,
    "Last_Estimation_in_Average_T_G": 10,
    "Last_Estimation_in_Average_T_L": 5,
    "First_Estimation_in_Average_T_G": 8,
    "First_Estimation_in_Average_T_L": 0,
    "Denoise_Classifier_Free_Guidence_Scale": 1
  },
  "logs": "Inverting...\n  0%|          | 0/4 [00:00<?, ?it/s]\n 25%|██▌       | 1/4 [00:00<00:01,  1.91it/s]\n 50%|█████     | 2/4 [00:00<00:00,  2.96it/s]\n 75%|███████▌  | 3/4 [00:00<00:00,  3.54it/s]\n100%|██████████| 4/4 [00:01<00:00,  3.96it/s]\n100%|██████████| 4/4 [00:01<00:00,  3.46it/s]\nGenerating...\n  0%|          | 0/4 [00:00<?, ?it/s]\n 50%|█████     | 2/4 [00:00<00:00, 14.75it/s]\n100%|██████████| 4/4 [00:00<00:00, 14.89it/s]\n100%|██████████| 4/4 [00:00<00:00, 14.86it/s]\nPopping cache",
  "metrics": {
    "predict_time": 2.37286,
    "total_time": 2.381383
  },
  "output": "https://replicate.delivery/pbxt/wkAyCeprZLxxcq0zjSvJyDCnObdJbGkPlYKDnmtxLypPMZRJA/image.png",
  "started_at": "2024-03-22T12:05:49.712960Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/6top3ftbacev7tfft7yk4no4za",
    "cancel": "https://api.replicate.com/v1/predictions/6top3ftbacev7tfft7yk4no4za/cancel"
  },
  "version": "bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a"
}

Generated in

2.4 seconds

Tweak it ShareReport