lucataco

flux-rf-inversion

Cold

Cog implementation of Diffusers Flux RFInversion Pipeline

Public

213 runs

Run with an API

Playground API Examples README Versions

Prediction

lucataco/flux-rf-inversion:5062c593200af97cb6a9271cb5a569bfd60ecbf3f66332adca983a7cff610810

Model

lucataco/flux-rf-inversion:5062c593

xfvr2b5gd9rmc0cm2mvajhbdw0

Status

Succeeded

Source

Web

Hardware

L40S

Total duration

33.5s

Created

9 months ago

Input

eta: 0.9
image
prompt: Portrait of a tiger
output_format: webp
stop_timestep: 0.38
output_quality: 80
start_timestep: 0
inversion_gamma: 0.5
num_inference_steps: 28

{
  "eta": 0.9,
  "image": "https://replicate.delivery/pbxt/MEQINqlsMs9i61oNXzOnsbsB5jV72H3u3ZWZUseGLSBfoZAC/cat.png",
  "prompt": "Portrait of a tiger",
  "output_format": "webp",
  "stop_timestep": 0.38,
  "output_quality": 80,
  "start_timestep": 0,
  "inversion_gamma": 0.5,
  "num_inference_steps": 28
}

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

const output = await replicate.run(
  "lucataco/flux-rf-inversion:5062c593200af97cb6a9271cb5a569bfd60ecbf3f66332adca983a7cff610810",
  {
    input: {
      eta: 0.9,
      image: "https://replicate.delivery/pbxt/MEQINqlsMs9i61oNXzOnsbsB5jV72H3u3ZWZUseGLSBfoZAC/cat.png",
      prompt: "Portrait of a tiger",
      output_format: "webp",
      stop_timestep: 0.38,
      output_quality: 80,
      start_timestep: 0,
      inversion_gamma: 0.5,
      num_inference_steps: 28
    }
  }
);

// 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

Import the client:

import replicate

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

output = replicate.run(
    "lucataco/flux-rf-inversion:5062c593200af97cb6a9271cb5a569bfd60ecbf3f66332adca983a7cff610810",
    input={
        "eta": 0.9,
        "image": "https://replicate.delivery/pbxt/MEQINqlsMs9i61oNXzOnsbsB5jV72H3u3ZWZUseGLSBfoZAC/cat.png",
        "prompt": "Portrait of a tiger",
        "output_format": "webp",
        "stop_timestep": 0.38,
        "output_quality": 80,
        "start_timestep": 0,
        "inversion_gamma": 0.5,
        "num_inference_steps": 28
    }
)

# 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.

Run lucataco/flux-rf-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": "lucataco/flux-rf-inversion:5062c593200af97cb6a9271cb5a569bfd60ecbf3f66332adca983a7cff610810",
    "input": {
      "eta": 0.9,
      "image": "https://replicate.delivery/pbxt/MEQINqlsMs9i61oNXzOnsbsB5jV72H3u3ZWZUseGLSBfoZAC/cat.png",
      "prompt": "Portrait of a tiger",
      "output_format": "webp",
      "stop_timestep": 0.38,
      "output_quality": 80,
      "start_timestep": 0,
      "inversion_gamma": 0.5,
      "num_inference_steps": 28
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2024-12-30T01:38:46.687423Z",
  "created_at": "2024-12-30T01:38:13.226000Z",
  "data_removed": false,
  "error": null,
  "id": "xfvr2b5gd9rmc0cm2mvajhbdw0",
  "input": {
    "eta": 0.9,
    "image": "https://replicate.delivery/pbxt/MEQINqlsMs9i61oNXzOnsbsB5jV72H3u3ZWZUseGLSBfoZAC/cat.png",
    "prompt": "Portrait of a tiger",
    "output_format": "webp",
    "stop_timestep": 0.38,
    "output_quality": 80,
    "start_timestep": 0,
    "inversion_gamma": 0.5,
    "num_inference_steps": 28
  },
  "logs": "Using seed: 14818\nPrompt: Portrait of a tiger\n  0%|          | 0/28 [00:00<?, ?it/s]\n  4%|▎         | 1/28 [00:00<00:09,  2.76it/s]\n  7%|▋         | 2/28 [00:00<00:12,  2.06it/s]\n 11%|█         | 3/28 [00:01<00:13,  1.91it/s]\n 14%|█▍        | 4/28 [00:02<00:13,  1.84it/s]\n 18%|█▊        | 5/28 [00:02<00:12,  1.81it/s]\n 21%|██▏       | 6/28 [00:03<00:12,  1.78it/s]\n 25%|██▌       | 7/28 [00:03<00:11,  1.77it/s]\n 29%|██▊       | 8/28 [00:04<00:11,  1.76it/s]\n 32%|███▏      | 9/28 [00:04<00:10,  1.76it/s]\n 36%|███▌      | 10/28 [00:05<00:10,  1.75it/s]\n 39%|███▉      | 11/28 [00:06<00:09,  1.74it/s]\n 43%|████▎     | 12/28 [00:06<00:09,  1.74it/s]\n 46%|████▋     | 13/28 [00:07<00:08,  1.74it/s]\n 50%|█████     | 14/28 [00:07<00:08,  1.73it/s]\n 54%|█████▎    | 15/28 [00:08<00:07,  1.73it/s]\n 57%|█████▋    | 16/28 [00:08<00:06,  1.73it/s]\n 61%|██████    | 17/28 [00:09<00:06,  1.73it/s]\n 64%|██████▍   | 18/28 [00:10<00:05,  1.73it/s]\n 68%|██████▊   | 19/28 [00:10<00:05,  1.73it/s]\n 71%|███████▏  | 20/28 [00:11<00:04,  1.73it/s]\n 75%|███████▌  | 21/28 [00:11<00:04,  1.73it/s]\n 79%|███████▊  | 22/28 [00:12<00:03,  1.72it/s]\n 82%|████████▏ | 23/28 [00:13<00:02,  1.72it/s]\n 86%|████████▌ | 24/28 [00:13<00:02,  1.72it/s]\n 89%|████████▉ | 25/28 [00:14<00:01,  1.72it/s]\n 93%|█████████▎| 26/28 [00:14<00:01,  1.73it/s]\n 96%|█████████▋| 27/28 [00:15<00:00,  1.73it/s]\n100%|██████████| 28/28 [00:15<00:00,  1.73it/s]\n100%|██████████| 28/28 [00:15<00:00,  1.76it/s]\n  0%|          | 0/28 [00:00<?, ?it/s]\n  4%|▎         | 1/28 [00:00<00:09,  2.74it/s]\n  7%|▋         | 2/28 [00:00<00:12,  2.04it/s]\n 11%|█         | 3/28 [00:01<00:13,  1.89it/s]\n 14%|█▍        | 4/28 [00:02<00:13,  1.83it/s]\n 18%|█▊        | 5/28 [00:02<00:12,  1.79it/s]\n 21%|██▏       | 6/28 [00:03<00:12,  1.77it/s]\n 25%|██▌       | 7/28 [00:03<00:11,  1.75it/s]\n 29%|██▊       | 8/28 [00:04<00:11,  1.75it/s]\n 32%|███▏      | 9/28 [00:04<00:10,  1.74it/s]\n 36%|███▌      | 10/28 [00:05<00:10,  1.74it/s]\n 39%|███▉      | 11/28 [00:06<00:09,  1.74it/s]\n 43%|████▎     | 12/28 [00:06<00:09,  1.74it/s]\n 46%|████▋     | 13/28 [00:07<00:08,  1.74it/s]\n 50%|█████     | 14/28 [00:07<00:08,  1.74it/s]\n 54%|█████▎    | 15/28 [00:08<00:07,  1.74it/s]\n 57%|█████▋    | 16/28 [00:09<00:06,  1.73it/s]\n 61%|██████    | 17/28 [00:09<00:06,  1.73it/s]\n 64%|██████▍   | 18/28 [00:10<00:05,  1.73it/s]\n 68%|██████▊   | 19/28 [00:10<00:05,  1.73it/s]\n 71%|███████▏  | 20/28 [00:11<00:04,  1.73it/s]\n 75%|███████▌  | 21/28 [00:11<00:04,  1.73it/s]\n 79%|███████▊  | 22/28 [00:12<00:03,  1.73it/s]\n 82%|████████▏ | 23/28 [00:13<00:02,  1.73it/s]\n 86%|████████▌ | 24/28 [00:13<00:02,  1.73it/s]\n 89%|████████▉ | 25/28 [00:14<00:01,  1.73it/s]\n 93%|█████████▎| 26/28 [00:14<00:01,  1.73it/s]\n 96%|█████████▋| 27/28 [00:15<00:00,  1.73it/s]\n100%|██████████| 28/28 [00:15<00:00,  1.72it/s]\n100%|██████████| 28/28 [00:15<00:00,  1.75it/s]",
  "metrics": {
    "predict_time": 33.454139486,
    "total_time": 33.461423
  },
  "output": [
    "https://replicate.delivery/xezq/nYz9ze8blnzlPqQLzjQsjfaWerQ8GNss1feUVukxy3t20VffJA/out-0.webp"
  ],
  "started_at": "2024-12-30T01:38:13.233284Z",
  "status": "succeeded",
  "urls": {
    "stream": "https://stream.replicate.com/v1/files/bcwr-5aqjqox7cptppiehzz4zxzme6o6bnhi2nf2hhb2ukpjdzobc6k5a",
    "get": "https://api.replicate.com/v1/predictions/xfvr2b5gd9rmc0cm2mvajhbdw0",
    "cancel": "https://api.replicate.com/v1/predictions/xfvr2b5gd9rmc0cm2mvajhbdw0/cancel"
  },
  "version": "5062c593200af97cb6a9271cb5a569bfd60ecbf3f66332adca983a7cff610810"
}

Generated in

33.5 seconds

Tweak it Iterate in playground ShareReport

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