adiba-shahana/sdxl-large-fine-tuned | Run with an API on Replicate

adiba-shahana / sdxl-large-fine-tuned

Warm

Public
84 runs
L40S
SDXL fine-tune

Iterate in playground

Run with an API

Playground API Examples README Versions

Input

prompt

string

Shift + Return to add a new line

In a style of tile, a mettalic finish modern marble design , elegant veinsIn a style of tile, a mettalic finish modern marble design , elegant veins

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

Preview

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: "K_EULER"

num_inference_steps

integer

(minimum: 1, maximum: 500)

Number of denoising steps

Default: 50

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

seed

integer

Random seed. Leave blank to randomize the seed

refine

string

Which refine style to use

Default: "no_refiner"

high_noise_frac

number

(minimum: 0, maximum: 1)

For expert_ensemble_refiner, the fraction of noise to use

Default: 0.8

refine_steps

integer

For base_image_refiner, the number of steps to refine, defaults to num_inference_steps

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

Default: false

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

npx create-replicate --model=adiba-shahana/sdxl-large-fine-tuned

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 adiba-shahana/sdxl-large-fine-tuned using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "adiba-shahana/sdxl-large-fine-tuned:8cbdc113b040bcb30e8a30846a1cbacbe315ff4970894376a81d6be91df5865f",
  {
    input: {
      seed: 1234,
      image: "https://replicate.delivery/pbxt/KS5oPMxDwH3eMjiiw82aZzUNKoyHQMbtRaj86J7SP4l29Fhj/generated_89-C-GS-ATBEDKF30A-ATLAS%20BEIGE%20DK%20FL%20A%20300X300MM.jpg.380x380_q85.jpg",
      width: 1024,
      height: 1024,
      prompt: "In a style of tile, a mettalic finish modern marble design , elegant veins",
      refine: "no_refiner",
      scheduler: "K_EULER",
      lora_scale: 0.6,
      num_outputs: 4,
      guidance_scale: 7.5,
      apply_watermark: true,
      high_noise_frac: 0.8,
      negative_prompt: "different color, low resolution",
      prompt_strength: 0.3,
      num_inference_steps: 50
    }
  }
);

// 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 adiba-shahana/sdxl-large-fine-tuned using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "adiba-shahana/sdxl-large-fine-tuned:8cbdc113b040bcb30e8a30846a1cbacbe315ff4970894376a81d6be91df5865f",
    input={
        "seed": 1234,
        "image": "https://replicate.delivery/pbxt/KS5oPMxDwH3eMjiiw82aZzUNKoyHQMbtRaj86J7SP4l29Fhj/generated_89-C-GS-ATBEDKF30A-ATLAS%20BEIGE%20DK%20FL%20A%20300X300MM.jpg.380x380_q85.jpg",
        "width": 1024,
        "height": 1024,
        "prompt": "In a style of tile, a mettalic finish modern marble design , elegant veins",
        "refine": "no_refiner",
        "scheduler": "K_EULER",
        "lora_scale": 0.6,
        "num_outputs": 4,
        "guidance_scale": 7.5,
        "apply_watermark": True,
        "high_noise_frac": 0.8,
        "negative_prompt": "different color, low resolution",
        "prompt_strength": 0.3,
        "num_inference_steps": 50
    }
)

# 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.

Set the REPLICATE_API_TOKEN environment variable:

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

Find your API token in your account settings.

Run adiba-shahana/sdxl-large-fine-tuned 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": "adiba-shahana/sdxl-large-fine-tuned:8cbdc113b040bcb30e8a30846a1cbacbe315ff4970894376a81d6be91df5865f",
    "input": {
      "seed": 1234,
      "image": "https://replicate.delivery/pbxt/KS5oPMxDwH3eMjiiw82aZzUNKoyHQMbtRaj86J7SP4l29Fhj/generated_89-C-GS-ATBEDKF30A-ATLAS%20BEIGE%20DK%20FL%20A%20300X300MM.jpg.380x380_q85.jpg",
      "width": 1024,
      "height": 1024,
      "prompt": "In a style of tile, a mettalic finish modern marble design , elegant veins",
      "refine": "no_refiner",
      "scheduler": "K_EULER",
      "lora_scale": 0.6,
      "num_outputs": 4,
      "guidance_scale": 7.5,
      "apply_watermark": true,
      "high_noise_frac": 0.8,
      "negative_prompt": "different color, low resolution",
      "prompt_strength": 0.3,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2024-02-23T05:43:31.513197Z",
  "created_at": "2024-02-23T05:43:15.521429Z",
  "data_removed": false,
  "error": null,
  "id": "rk3pey3bdeaqcgx6ucfrfuk6ee",
  "input": {
    "seed": 1234,
    "image": "https://replicate.delivery/pbxt/KS5oPMxDwH3eMjiiw82aZzUNKoyHQMbtRaj86J7SP4l29Fhj/generated_89-C-GS-ATBEDKF30A-ATLAS%20BEIGE%20DK%20FL%20A%20300X300MM.jpg.380x380_q85.jpg",
    "width": 1024,
    "height": 1024,
    "prompt": "In a style of tile, a mettalic finish modern marble design , elegant veins",
    "refine": "no_refiner",
    "scheduler": "K_EULER",
    "lora_scale": 0.6,
    "num_outputs": 4,
    "guidance_scale": 7.5,
    "apply_watermark": true,
    "high_noise_frac": 0.8,
    "negative_prompt": "different color, low resolution",
    "prompt_strength": 0.3,
    "num_inference_steps": 50
  },
  "logs": "Using seed: 1234\nEnsuring enough disk space...\nFree disk space: 1362282278912\nDownloading weights: https://replicate.delivery/pbxt/EyTpk37hR16ZHhNSoTbJ05W691fn0f3eHSnlZbuvWDjBJRykA/trained_model.tar\n2024-02-23T05:43:19Z | INFO  | [ Initiating ] dest=/src/weights-cache/800713987ecee3b0 minimum_chunk_size=150M url=https://replicate.delivery/pbxt/EyTpk37hR16ZHhNSoTbJ05W691fn0f3eHSnlZbuvWDjBJRykA/trained_model.tar\n2024-02-23T05:43:26Z | INFO  | [ Complete ] dest=/src/weights-cache/800713987ecee3b0 size=\"186 MB\" total_elapsed=6.381s url=https://replicate.delivery/pbxt/EyTpk37hR16ZHhNSoTbJ05W691fn0f3eHSnlZbuvWDjBJRykA/trained_model.tar\nb''\nDownloaded weights in 6.5203540325164795 seconds\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: In a style of tile, a mettalic finish modern marble design , elegant veins\nimg2img mode\n  0%|          | 0/15 [00:00<?, ?it/s]\n  7%|▋         | 1/15 [00:00<00:02,  4.89it/s]\n 13%|█▎        | 2/15 [00:00<00:02,  5.60it/s]\n 20%|██        | 3/15 [00:00<00:02,  5.84it/s]\n 27%|██▋       | 4/15 [00:00<00:01,  5.96it/s]\n 33%|███▎      | 5/15 [00:00<00:01,  6.03it/s]\n 40%|████      | 6/15 [00:01<00:01,  6.08it/s]\n 47%|████▋     | 7/15 [00:01<00:01,  6.10it/s]\n 53%|█████▎    | 8/15 [00:01<00:01,  6.14it/s]\n 60%|██████    | 9/15 [00:01<00:00,  6.16it/s]\n 67%|██████▋   | 10/15 [00:01<00:00,  6.17it/s]\n 73%|███████▎  | 11/15 [00:01<00:00,  6.18it/s]\n 80%|████████  | 12/15 [00:01<00:00,  6.18it/s]\n 87%|████████▋ | 13/15 [00:02<00:00,  6.19it/s]\n 93%|█████████▎| 14/15 [00:02<00:00,  6.19it/s]\n100%|██████████| 15/15 [00:02<00:00,  6.19it/s]\n100%|██████████| 15/15 [00:02<00:00,  6.08it/s]\nPotential NSFW content was detected in one or more images. A black image will be returned instead. Try again with a different prompt and/or seed.\nNSFW content detected in image 0",
  "metrics": {
    "predict_time": 12.230371,
    "total_time": 15.991768
  },
  "output": [
    "https://replicate.delivery/pbxt/YV3LPaSebw2gBCQVhmOlN9BQoL1CBWLeGbeT4WfweUQNQxLTC/out-1.png",
    "https://replicate.delivery/pbxt/X9VfSPa9ZBxkd6emHVBylfjOalbwtYQ1juJnGJ5flFqJo4lJB/out-2.png",
    "https://replicate.delivery/pbxt/aZtQE7UzUU6GN1VZdA2fYX3MaTeYnMznwmS6GCh7Ld2DKeykA/out-3.png"
  ],
  "started_at": "2024-02-23T05:43:19.282826Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/rk3pey3bdeaqcgx6ucfrfuk6ee",
    "cancel": "https://api.replicate.com/v1/predictions/rk3pey3bdeaqcgx6ucfrfuk6ee/cancel"
  },
  "version": "49385a24fadb595a10ef6ec6425ef3f07781ba611ec33b0bad66cff8ae41abcb"
}

Generated in

12.2 seconds

Tweak itReport View full prediction

Using seed: 1234
Ensuring enough disk space...
Free disk space: 1362282278912
Downloading weights: https://replicate.delivery/pbxt/EyTpk37hR16ZHhNSoTbJ05W691fn0f3eHSnlZbuvWDjBJRykA/trained_model.tar
2024-02-23T05:43:19Z | INFO  | [ Initiating ] dest=/src/weights-cache/800713987ecee3b0 minimum_chunk_size=150M url=https://replicate.delivery/pbxt/EyTpk37hR16ZHhNSoTbJ05W691fn0f3eHSnlZbuvWDjBJRykA/trained_model.tar
2024-02-23T05:43:26Z | INFO  | [ Complete ] dest=/src/weights-cache/800713987ecee3b0 size="186 MB" total_elapsed=6.381s url=https://replicate.delivery/pbxt/EyTpk37hR16ZHhNSoTbJ05W691fn0f3eHSnlZbuvWDjBJRykA/trained_model.tar
b''
Downloaded weights in 6.5203540325164795 seconds
Loading fine-tuned model
Does not have Unet. assume we are using LoRA
Loading Unet LoRA
Prompt: In a style of tile, a mettalic finish modern marble design , elegant veins
img2img mode
  0%|          | 0/15 [00:00<?, ?it/s]
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 20%|██        | 3/15 [00:00<00:02,  5.84it/s]
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100%|██████████| 15/15 [00:02<00:00,  6.08it/s]
Potential NSFW content was detected in one or more images. A black image will be returned instead. Try again with a different prompt and/or seed.
NSFW content detected in image 0

This output was created using a different version of the model, adiba-shahana/sdxl-large-fine-tuned:49385a24.

Examples

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Run time and cost

This model runs on Nvidia L40S GPU hardware. We don't yet have enough runs of this model to provide performance information.

Readme

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