fofr

flux-goya-black-painting

Warm

Flux fine tuned on the 14 black paintings by Goya

Public

1.3K runs

H100

Run with an API

Pricing

Playground API Examples README Versions

Prediction

fofr/flux-goya-black-painting:4397451875078097f24c31b2ab8e1fec1adfbfa2ae63567be6fa8bf162a0ac58

Model

fofr/flux-goya-black-painting:43974518

aa1n6sy89srma0ckvg0b570pf8

Status

Succeeded

Source

Web

Hardware

H100

Total duration

6.3s

Created

8 months ago

Input

model: dev
prompt: a moody GOYA_BLK_PAINTING portrait painting of a gnarly man
go_fast
lora_scale: 1
megapixels: 1
num_outputs: 1
aspect_ratio: 3:2
output_format: webp
guidance_scale: 3
output_quality: 80
prompt_strength: 0.8
extra_lora_scale: 1
num_inference_steps: 28

{
  "model": "dev",
  "prompt": "a moody GOYA_BLK_PAINTING portrait painting of a gnarly man",
  "go_fast": false,
  "lora_scale": 1,
  "megapixels": "1",
  "num_outputs": 1,
  "aspect_ratio": "3:2",
  "output_format": "webp",
  "guidance_scale": 3,
  "output_quality": 80,
  "prompt_strength": 0.8,
  "extra_lora_scale": 1,
  "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 fofr/flux-goya-black-painting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "fofr/flux-goya-black-painting:4397451875078097f24c31b2ab8e1fec1adfbfa2ae63567be6fa8bf162a0ac58",
  {
    input: {
      model: "dev",
      prompt: "a moody GOYA_BLK_PAINTING portrait painting of a gnarly man",
      go_fast: false,
      lora_scale: 1,
      megapixels: "1",
      num_outputs: 1,
      aspect_ratio: "3:2",
      output_format: "webp",
      guidance_scale: 3,
      output_quality: 80,
      prompt_strength: 0.8,
      extra_lora_scale: 1,
      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 fofr/flux-goya-black-painting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "fofr/flux-goya-black-painting:4397451875078097f24c31b2ab8e1fec1adfbfa2ae63567be6fa8bf162a0ac58",
    input={
        "model": "dev",
        "prompt": "a moody GOYA_BLK_PAINTING portrait painting of a gnarly man",
        "go_fast": False,
        "lora_scale": 1,
        "megapixels": "1",
        "num_outputs": 1,
        "aspect_ratio": "3:2",
        "output_format": "webp",
        "guidance_scale": 3,
        "output_quality": 80,
        "prompt_strength": 0.8,
        "extra_lora_scale": 1,
        "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 fofr/flux-goya-black-painting 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": "fofr/flux-goya-black-painting:4397451875078097f24c31b2ab8e1fec1adfbfa2ae63567be6fa8bf162a0ac58",
    "input": {
      "model": "dev",
      "prompt": "a moody GOYA_BLK_PAINTING portrait painting of a gnarly man",
      "go_fast": false,
      "lora_scale": 1,
      "megapixels": "1",
      "num_outputs": 1,
      "aspect_ratio": "3:2",
      "output_format": "webp",
      "guidance_scale": 3,
      "output_quality": 80,
      "prompt_strength": 0.8,
      "extra_lora_scale": 1,
      "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": "2024-12-18T23:01:05.332168Z",
  "created_at": "2024-12-18T23:00:59.086000Z",
  "data_removed": false,
  "error": null,
  "id": "aa1n6sy89srma0ckvg0b570pf8",
  "input": {
    "model": "dev",
    "prompt": "a moody GOYA_BLK_PAINTING portrait painting of a gnarly man",
    "go_fast": false,
    "lora_scale": 1,
    "megapixels": "1",
    "num_outputs": 1,
    "aspect_ratio": "3:2",
    "output_format": "webp",
    "guidance_scale": 3,
    "output_quality": 80,
    "prompt_strength": 0.8,
    "extra_lora_scale": 1,
    "num_inference_steps": 28
  },
  "logs": "2024-12-18 23:00:59.181 | DEBUG    | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2024-12-18 23:00:59.181 | DEBUG    | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA:   0%|          | 0/304 [00:00<?, ?it/s]\nApplying LoRA:  93%|█████████▎| 284/304 [00:00<00:00, 2827.85it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2731.00it/s]\n2024-12-18 23:00:59.293 | SUCCESS  | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s\n2024-12-18 23:00:59.295 | INFO     | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/efcf5096661906c3\n2024-12-18 23:00:59.414 | INFO     | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2024-12-18 23:00:59.414 | DEBUG    | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2024-12-18 23:00:59.414 | DEBUG    | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA:   0%|          | 0/304 [00:00<?, ?it/s]\nApplying LoRA:  93%|█████████▎| 284/304 [00:00<00:00, 2832.23it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2736.26it/s]\n2024-12-18 23:00:59.526 | SUCCESS  | fp8.lora_loading:load_lora:539 - LoRA applied in 0.23s\nUsing seed: 27861\n0it [00:00, ?it/s]\n1it [00:00,  8.90it/s]\n2it [00:00,  6.27it/s]\n3it [00:00,  5.67it/s]\n4it [00:00,  5.42it/s]\n5it [00:00,  5.29it/s]\n6it [00:01,  5.18it/s]\n7it [00:01,  5.12it/s]\n8it [00:01,  5.10it/s]\n9it [00:01,  5.10it/s]\n10it [00:01,  5.10it/s]\n11it [00:02,  5.09it/s]\n12it [00:02,  5.07it/s]\n13it [00:02,  5.07it/s]\n14it [00:02,  5.07it/s]\n15it [00:02,  5.08it/s]\n16it [00:03,  5.08it/s]\n17it [00:03,  5.08it/s]\n18it [00:03,  5.06it/s]\n19it [00:03,  5.06it/s]\n20it [00:03,  5.07it/s]\n21it [00:04,  5.07it/s]\n22it [00:04,  5.07it/s]\n23it [00:04,  5.06it/s]\n24it [00:04,  5.06it/s]\n25it [00:04,  5.06it/s]\n26it [00:05,  5.06it/s]\n27it [00:05,  5.06it/s]\n28it [00:05,  5.06it/s]\n28it [00:05,  5.15it/s]\nTotal safe images: 1 out of 1",
  "metrics": {
    "predict_time": 6.149917999,
    "total_time": 6.246168
  },
  "output": [
    "https://replicate.delivery/xezq/ezZ5uaI3p6VbBin2PLJGwUgXbTp7Tw9TghifxrwgzKeixg4nA/out-0.webp"
  ],
  "started_at": "2024-12-18T23:00:59.182250Z",
  "status": "succeeded",
  "urls": {
    "stream": "https://stream.replicate.com/v1/files/bcwr-h5vpj7t3yxm3pyz7yqv5jwnc7fhlwjlyksae3pr25wxdoiy2pixq",
    "get": "https://api.replicate.com/v1/predictions/aa1n6sy89srma0ckvg0b570pf8",
    "cancel": "https://api.replicate.com/v1/predictions/aa1n6sy89srma0ckvg0b570pf8/cancel"
  },
  "version": "4397451875078097f24c31b2ab8e1fec1adfbfa2ae63567be6fa8bf162a0ac58"
}

Generated in

6.2 seconds

Tweak it Iterate in playground Share Report

2024-12-18 23:00:59.181 | DEBUG    | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2024-12-18 23:00:59.181 | DEBUG    | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA:   0%|          | 0/304 [00:00<?, ?it/s]
Applying LoRA:  93%|█████████▎| 284/304 [00:00<00:00, 2827.85it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2731.00it/s]
2024-12-18 23:00:59.293 | SUCCESS  | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s
2024-12-18 23:00:59.295 | INFO     | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/efcf5096661906c3
2024-12-18 23:00:59.414 | INFO     | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded
2024-12-18 23:00:59.414 | DEBUG    | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2024-12-18 23:00:59.414 | DEBUG    | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA:   0%|          | 0/304 [00:00<?, ?it/s]
Applying LoRA:  93%|█████████▎| 284/304 [00:00<00:00, 2832.23it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2736.26it/s]
2024-12-18 23:00:59.526 | SUCCESS  | fp8.lora_loading:load_lora:539 - LoRA applied in 0.23s
Using seed: 27861
0it [00:00, ?it/s]
1it [00:00,  8.90it/s]
2it [00:00,  6.27it/s]
3it [00:00,  5.67it/s]
4it [00:00,  5.42it/s]
5it [00:00,  5.29it/s]
6it [00:01,  5.18it/s]
7it [00:01,  5.12it/s]
8it [00:01,  5.10it/s]
9it [00:01,  5.10it/s]
10it [00:01,  5.10it/s]
11it [00:02,  5.09it/s]
12it [00:02,  5.07it/s]
13it [00:02,  5.07it/s]
14it [00:02,  5.07it/s]
15it [00:02,  5.08it/s]
16it [00:03,  5.08it/s]
17it [00:03,  5.08it/s]
18it [00:03,  5.06it/s]
19it [00:03,  5.06it/s]
20it [00:03,  5.07it/s]
21it [00:04,  5.07it/s]
22it [00:04,  5.07it/s]
23it [00:04,  5.06it/s]
24it [00:04,  5.06it/s]
25it [00:04,  5.06it/s]
26it [00:05,  5.06it/s]
27it [00:05,  5.06it/s]
28it [00:05,  5.06it/s]
28it [00:05,  5.15it/s]
Total safe images: 1 out of 1

Prediction

fofr/flux-goya-black-painting:4397451875078097f24c31b2ab8e1fec1adfbfa2ae63567be6fa8bf162a0ac58

Model

fofr/flux-goya-black-painting:43974518

1wmz9g90g5rma0ckvg0vs1t0h8

Status

Succeeded

Source

Web

Hardware

H100

Total duration

5.8s

Created

8 months ago

Input

model: dev
prompt: a moody GOYA_BLK_PAINTING portrait painting of a gnarly man on his laptop
go_fast
lora_scale: 1
megapixels: 1
num_outputs: 1
aspect_ratio: 3:2
output_format: webp
guidance_scale: 3
output_quality: 80
prompt_strength: 0.8
extra_lora_scale: 1
num_inference_steps: 28

{
  "model": "dev",
  "prompt": "a moody GOYA_BLK_PAINTING portrait painting of a gnarly man on his laptop",
  "go_fast": false,
  "lora_scale": 1,
  "megapixels": "1",
  "num_outputs": 1,
  "aspect_ratio": "3:2",
  "output_format": "webp",
  "guidance_scale": 3,
  "output_quality": 80,
  "prompt_strength": 0.8,
  "extra_lora_scale": 1,
  "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 fofr/flux-goya-black-painting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "fofr/flux-goya-black-painting:4397451875078097f24c31b2ab8e1fec1adfbfa2ae63567be6fa8bf162a0ac58",
  {
    input: {
      model: "dev",
      prompt: "a moody GOYA_BLK_PAINTING portrait painting of a gnarly man on his laptop",
      go_fast: false,
      lora_scale: 1,
      megapixels: "1",
      num_outputs: 1,
      aspect_ratio: "3:2",
      output_format: "webp",
      guidance_scale: 3,
      output_quality: 80,
      prompt_strength: 0.8,
      extra_lora_scale: 1,
      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 fofr/flux-goya-black-painting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "fofr/flux-goya-black-painting:4397451875078097f24c31b2ab8e1fec1adfbfa2ae63567be6fa8bf162a0ac58",
    input={
        "model": "dev",
        "prompt": "a moody GOYA_BLK_PAINTING portrait painting of a gnarly man on his laptop",
        "go_fast": False,
        "lora_scale": 1,
        "megapixels": "1",
        "num_outputs": 1,
        "aspect_ratio": "3:2",
        "output_format": "webp",
        "guidance_scale": 3,
        "output_quality": 80,
        "prompt_strength": 0.8,
        "extra_lora_scale": 1,
        "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 fofr/flux-goya-black-painting 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": "fofr/flux-goya-black-painting:4397451875078097f24c31b2ab8e1fec1adfbfa2ae63567be6fa8bf162a0ac58",
    "input": {
      "model": "dev",
      "prompt": "a moody GOYA_BLK_PAINTING portrait painting of a gnarly man on his laptop",
      "go_fast": false,
      "lora_scale": 1,
      "megapixels": "1",
      "num_outputs": 1,
      "aspect_ratio": "3:2",
      "output_format": "webp",
      "guidance_scale": 3,
      "output_quality": 80,
      "prompt_strength": 0.8,
      "extra_lora_scale": 1,
      "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": "2024-12-18T23:01:27.494421Z",
  "created_at": "2024-12-18T23:01:21.665000Z",
  "data_removed": false,
  "error": null,
  "id": "1wmz9g90g5rma0ckvg0vs1t0h8",
  "input": {
    "model": "dev",
    "prompt": "a moody GOYA_BLK_PAINTING portrait painting of a gnarly man on his laptop",
    "go_fast": false,
    "lora_scale": 1,
    "megapixels": "1",
    "num_outputs": 1,
    "aspect_ratio": "3:2",
    "output_format": "webp",
    "guidance_scale": 3,
    "output_quality": 80,
    "prompt_strength": 0.8,
    "extra_lora_scale": 1,
    "num_inference_steps": 28
  },
  "logs": "Lora https://replicate.delivery/xezq/ZQyQUTjJY6qnEFfcTS7fsbKxZozmVEg9j3hchBf74RbOdg4nA/trained_model.tar already loaded\nUsing seed: 5872\n0it [00:00, ?it/s]\n1it [00:00,  8.79it/s]\n2it [00:00,  6.11it/s]\n3it [00:00,  5.57it/s]\n4it [00:00,  5.35it/s]\n5it [00:00,  5.21it/s]\n6it [00:01,  5.11it/s]\n7it [00:01,  5.08it/s]\n8it [00:01,  5.07it/s]\n9it [00:01,  5.05it/s]\n10it [00:01,  5.03it/s]\n11it [00:02,  5.00it/s]\n12it [00:02,  4.99it/s]\n13it [00:02,  4.99it/s]\n14it [00:02,  5.00it/s]\n15it [00:02,  5.00it/s]\n16it [00:03,  4.99it/s]\n17it [00:03,  4.98it/s]\n18it [00:03,  4.98it/s]\n19it [00:03,  4.99it/s]\n20it [00:03,  4.99it/s]\n21it [00:04,  4.99it/s]\n22it [00:04,  5.00it/s]\n23it [00:04,  4.99it/s]\n24it [00:04,  4.99it/s]\n25it [00:04,  4.99it/s]\n26it [00:05,  4.99it/s]\n27it [00:05,  5.00it/s]\n28it [00:05,  5.00it/s]\n28it [00:05,  5.07it/s]\nTotal safe images: 1 out of 1",
  "metrics": {
    "predict_time": 5.823375568,
    "total_time": 5.829421
  },
  "output": [
    "https://replicate.delivery/xezq/0eLKCVneLHjOAkCL9Ck8OiSr2UexybuLPg3ffKa5Ryu5IDifE/out-0.webp"
  ],
  "started_at": "2024-12-18T23:01:21.671046Z",
  "status": "succeeded",
  "urls": {
    "stream": "https://stream.replicate.com/v1/files/bcwr-llw2ckv35j525lm24eewusuvewqxvvackrm74ky2enn4nq5bspqq",
    "get": "https://api.replicate.com/v1/predictions/1wmz9g90g5rma0ckvg0vs1t0h8",
    "cancel": "https://api.replicate.com/v1/predictions/1wmz9g90g5rma0ckvg0vs1t0h8/cancel"
  },
  "version": "4397451875078097f24c31b2ab8e1fec1adfbfa2ae63567be6fa8bf162a0ac58"
}

Generated in

5.8 seconds

Tweak it Iterate in playground Share Report

Want to make some of these yourself?

Run this model

Prediction

Input

Output

Prediction

Input

Output

Logs (aa1n6sy89srma0ckvg0b570pf8)

Logs (1wmz9g90g5rma0ckvg0vs1t0h8)