cesarvega / my-alinamodel

{
  "image": "https://replicate.delivery/pbxt/MSqRqKKjETReKFWgtcb68G09HGFjBeLK7qUSDslgHX6LmwCc/Screenshot%202025-02-08%20104902.png",
  "model": "dev",
  "prompt": "a photo of alina in the beach of Miami",
  "go_fast": false,
  "lora_scale": 1,
  "megapixels": "1",
  "num_outputs": 1,
  "aspect_ratio": "1:1",
  "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 cesarvega/my-alinamodel using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "cesarvega/my-alinamodel:54cc655616e24a8f59010c48d351ce1192c0581885ffcb839be388309f0a85af",
  {
    input: {
      image: "https://replicate.delivery/pbxt/MSqRqKKjETReKFWgtcb68G09HGFjBeLK7qUSDslgHX6LmwCc/Screenshot%202025-02-08%20104902.png",
      model: "dev",
      prompt: "a photo of alina in the beach of Miami",
      go_fast: false,
      lora_scale: 1,
      megapixels: "1",
      num_outputs: 1,
      aspect_ratio: "1:1",
      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 cesarvega/my-alinamodel using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "cesarvega/my-alinamodel:54cc655616e24a8f59010c48d351ce1192c0581885ffcb839be388309f0a85af",
    input={
        "image": "https://replicate.delivery/pbxt/MSqRqKKjETReKFWgtcb68G09HGFjBeLK7qUSDslgHX6LmwCc/Screenshot%202025-02-08%20104902.png",
        "model": "dev",
        "prompt": "a photo of alina in the beach of Miami",
        "go_fast": False,
        "lora_scale": 1,
        "megapixels": "1",
        "num_outputs": 1,
        "aspect_ratio": "1:1",
        "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 cesarvega/my-alinamodel 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": "cesarvega/my-alinamodel:54cc655616e24a8f59010c48d351ce1192c0581885ffcb839be388309f0a85af",
    "input": {
      "image": "https://replicate.delivery/pbxt/MSqRqKKjETReKFWgtcb68G09HGFjBeLK7qUSDslgHX6LmwCc/Screenshot%202025-02-08%20104902.png",
      "model": "dev",
      "prompt": "a photo of alina in the beach of Miami",
      "go_fast": false,
      "lora_scale": 1,
      "megapixels": "1",
      "num_outputs": 1,
      "aspect_ratio": "1:1",
      "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": "2025-02-08T16:42:43.509615Z",
  "created_at": "2025-02-08T16:42:34.446000Z",
  "data_removed": false,
  "error": null,
  "id": "f0mgt5069srme0cmwsrrtfhebg",
  "input": {
    "image": "https://replicate.delivery/pbxt/MSqRqKKjETReKFWgtcb68G09HGFjBeLK7qUSDslgHX6LmwCc/Screenshot%202025-02-08%20104902.png",
    "model": "dev",
    "prompt": "a photo of alina in the beach of Miami",
    "go_fast": false,
    "lora_scale": 1,
    "megapixels": "1",
    "num_outputs": 1,
    "aspect_ratio": "1:1",
    "output_format": "webp",
    "guidance_scale": 3,
    "output_quality": 80,
    "prompt_strength": 0.8,
    "extra_lora_scale": 1,
    "num_inference_steps": 28
  },
  "logs": "free=29256104157184\nDownloading weights\n2025-02-08T16:42:34Z | INFO  | [ Initiating ] chunk_size=150M dest=/tmp/tmp22mkhgvr/weights url=https://replicate.delivery/xezq/NDkfE21qfzlV4kQGGq6siQqzERgXl54cEkh7gLERIH9wpTNUA/trained_model.tar\n2025-02-08T16:42:37Z | INFO  | [ Complete ] dest=/tmp/tmp22mkhgvr/weights size=\"172 MB\" total_elapsed=2.395s url=https://replicate.delivery/xezq/NDkfE21qfzlV4kQGGq6siQqzERgXl54cEkh7gLERIH9wpTNUA/trained_model.tar\nDownloaded weights in 2.42s\nLoaded LoRAs in 2.96s\nUsing seed: 31295\nPrompt: a photo of alina in the beach of Miami\n[!] Resizing input image from 863x847 to 864x848\n[!] img2img mode\n  0%|          | 0/23 [00:00<?, ?it/s]\n  4%|▍         | 1/23 [00:00<00:18,  1.19it/s]\n  9%|▊         | 2/23 [00:01<00:09,  2.20it/s]\n 13%|█▎        | 3/23 [00:01<00:06,  3.02it/s]\n 17%|█▋        | 4/23 [00:01<00:05,  3.65it/s]\n 22%|██▏       | 5/23 [00:01<00:04,  4.13it/s]\n 26%|██▌       | 6/23 [00:01<00:03,  4.49it/s]\n 30%|███       | 7/23 [00:01<00:03,  4.75it/s]\n 35%|███▍      | 8/23 [00:02<00:03,  4.94it/s]\n 39%|███▉      | 9/23 [00:02<00:02,  5.07it/s]\n 43%|████▎     | 10/23 [00:02<00:02,  5.16it/s]\n 48%|████▊     | 11/23 [00:02<00:02,  5.23it/s]\n 52%|█████▏    | 12/23 [00:02<00:02,  5.28it/s]\n 57%|█████▋    | 13/23 [00:03<00:01,  5.31it/s]\n 61%|██████    | 14/23 [00:03<00:01,  5.34it/s]\n 65%|██████▌   | 15/23 [00:03<00:01,  5.35it/s]\n 70%|██████▉   | 16/23 [00:03<00:01,  5.36it/s]\n 74%|███████▍  | 17/23 [00:03<00:01,  5.37it/s]\n 78%|███████▊  | 18/23 [00:03<00:00,  5.38it/s]\n 83%|████████▎ | 19/23 [00:04<00:00,  5.38it/s]\n 87%|████████▋ | 20/23 [00:04<00:00,  5.39it/s]\n 91%|█████████▏| 21/23 [00:04<00:00,  5.39it/s]\n 96%|█████████▌| 22/23 [00:04<00:00,  5.39it/s]\n100%|██████████| 23/23 [00:04<00:00,  5.39it/s]\n100%|██████████| 23/23 [00:04<00:00,  4.68it/s]\nTotal safe images: 1 out of 1",
  "metrics": {
    "predict_time": 8.880737427,
    "total_time": 9.063615
  },
  "output": [
    "https://replicate.delivery/xezq/Qwwf2R2jbfuSlkMWJVVhnqfiSKufWhXBEvOE8SK6ZyAN4O1QB/out-0.webp"
  ],
  "started_at": "2025-02-08T16:42:34.628878Z",
  "status": "succeeded",
  "urls": {
    "stream": "https://stream.replicate.com/v1/files/bcwr-x75f5vhuduuutvyy3lsmcynzgjspxqeylbsuycjkye57hzgxwiga",
    "get": "https://api.replicate.com/v1/predictions/f0mgt5069srme0cmwsrrtfhebg",
    "cancel": "https://api.replicate.com/v1/predictions/f0mgt5069srme0cmwsrrtfhebg/cancel"
  },
  "version": "54cc655616e24a8f59010c48d351ce1192c0581885ffcb839be388309f0a85af"
}

Generated in

8.9 seconds

Tweak it ShareReport

free=29256104157184
Downloading weights
2025-02-08T16:42:34Z | INFO  | [ Initiating ] chunk_size=150M dest=/tmp/tmp22mkhgvr/weights url=https://replicate.delivery/xezq/NDkfE21qfzlV4kQGGq6siQqzERgXl54cEkh7gLERIH9wpTNUA/trained_model.tar
2025-02-08T16:42:37Z | INFO  | [ Complete ] dest=/tmp/tmp22mkhgvr/weights size="172 MB" total_elapsed=2.395s url=https://replicate.delivery/xezq/NDkfE21qfzlV4kQGGq6siQqzERgXl54cEkh7gLERIH9wpTNUA/trained_model.tar
Downloaded weights in 2.42s
Loaded LoRAs in 2.96s
Using seed: 31295
Prompt: a photo of alina in the beach of Miami
[!] Resizing input image from 863x847 to 864x848
[!] img2img mode
  0%|          | 0/23 [00:00<?, ?it/s]
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 61%|██████    | 14/23 [00:03<00:01,  5.34it/s]
 65%|██████▌   | 15/23 [00:03<00:01,  5.35it/s]
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 78%|███████▊  | 18/23 [00:03<00:00,  5.38it/s]
 83%|████████▎ | 19/23 [00:04<00:00,  5.38it/s]
 87%|████████▋ | 20/23 [00:04<00:00,  5.39it/s]
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 96%|█████████▌| 22/23 [00:04<00:00,  5.39it/s]
100%|██████████| 23/23 [00:04<00:00,  5.39it/s]
100%|██████████| 23/23 [00:04<00:00,  4.68it/s]
Total safe images: 1 out of 1

Prediction

cesarvega/my-alinamodel:54cc655616e24a8f59010c48d351ce1192c0581885ffcb839be388309f0a85af

Model

cesarvega/my-alinamodel:54cc6556

cz134hgbthrm80cmwsxbq1gvv8

Status

Succeeded

Source

Web

Hardware

H100

Total duration

7.3s

Created

5 months ago

Input

model: dev
prompt: a photo of alina in an short green construction worker vest and bathing suit and helmet
go_fast
lora_scale: 1
megapixels: 1
num_outputs: 1
aspect_ratio: 1:1
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 photo of alina in an short green construction worker vest and bathing suit and helmet",
  "go_fast": false,
  "lora_scale": 1,
  "megapixels": "1",
  "num_outputs": 1,
  "aspect_ratio": "1:1",
  "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 cesarvega/my-alinamodel using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "cesarvega/my-alinamodel:54cc655616e24a8f59010c48d351ce1192c0581885ffcb839be388309f0a85af",
  {
    input: {
      model: "dev",
      prompt: "a photo of alina in an short green construction worker vest and bathing suit and helmet",
      go_fast: false,
      lora_scale: 1,
      megapixels: "1",
      num_outputs: 1,
      aspect_ratio: "1:1",
      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 cesarvega/my-alinamodel using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "cesarvega/my-alinamodel:54cc655616e24a8f59010c48d351ce1192c0581885ffcb839be388309f0a85af",
    input={
        "model": "dev",
        "prompt": "a photo of alina in an short green construction worker vest and bathing suit and helmet",
        "go_fast": False,
        "lora_scale": 1,
        "megapixels": "1",
        "num_outputs": 1,
        "aspect_ratio": "1:1",
        "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 cesarvega/my-alinamodel 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": "cesarvega/my-alinamodel:54cc655616e24a8f59010c48d351ce1192c0581885ffcb839be388309f0a85af",
    "input": {
      "model": "dev",
      "prompt": "a photo of alina in an short green construction worker vest and bathing suit and helmet",
      "go_fast": false,
      "lora_scale": 1,
      "megapixels": "1",
      "num_outputs": 1,
      "aspect_ratio": "1:1",
      "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": "2025-02-08T16:52:32.939479Z",
  "created_at": "2025-02-08T16:52:25.684000Z",
  "data_removed": false,
  "error": null,
  "id": "cz134hgbthrm80cmwsxbq1gvv8",
  "input": {
    "model": "dev",
    "prompt": "a photo of alina in an short green construction worker vest and bathing suit and helmet",
    "go_fast": false,
    "lora_scale": 1,
    "megapixels": "1",
    "num_outputs": 1,
    "aspect_ratio": "1:1",
    "output_format": "webp",
    "guidance_scale": 3,
    "output_quality": 80,
    "prompt_strength": 0.8,
    "extra_lora_scale": 1,
    "num_inference_steps": 28
  },
  "logs": "Weights already loaded\nLoaded LoRAs in 0.02s\nUsing seed: 53106\nPrompt: a photo of alina in an short green construction worker vest and bathing suit and helmet\n[!] txt2img mode\n  0%|          | 0/28 [00:00<?, ?it/s]\n  4%|▎         | 1/28 [00:00<00:06,  4.01it/s]\n  7%|▋         | 2/28 [00:00<00:05,  4.53it/s]\n 11%|█         | 3/28 [00:00<00:05,  4.27it/s]\n 14%|█▍        | 4/28 [00:00<00:05,  4.16it/s]\n 18%|█▊        | 5/28 [00:01<00:05,  4.09it/s]\n 21%|██▏       | 6/28 [00:01<00:05,  4.06it/s]\n 25%|██▌       | 7/28 [00:01<00:05,  4.04it/s]\n 29%|██▊       | 8/28 [00:01<00:04,  4.03it/s]\n 32%|███▏      | 9/28 [00:02<00:04,  4.02it/s]\n 36%|███▌      | 10/28 [00:02<00:04,  4.01it/s]\n 39%|███▉      | 11/28 [00:02<00:04,  4.01it/s]\n 43%|████▎     | 12/28 [00:02<00:03,  4.00it/s]\n 46%|████▋     | 13/28 [00:03<00:03,  4.00it/s]\n 50%|█████     | 14/28 [00:03<00:03,  3.99it/s]\n 54%|█████▎    | 15/28 [00:03<00:03,  4.00it/s]\n 57%|█████▋    | 16/28 [00:03<00:03,  4.00it/s]\n 61%|██████    | 17/28 [00:04<00:02,  4.00it/s]\n 64%|██████▍   | 18/28 [00:04<00:02,  3.99it/s]\n 68%|██████▊   | 19/28 [00:04<00:02,  3.99it/s]\n 71%|███████▏  | 20/28 [00:04<00:02,  3.99it/s]\n 75%|███████▌  | 21/28 [00:05<00:01,  3.99it/s]\n 79%|███████▊  | 22/28 [00:05<00:01,  4.00it/s]\n 82%|████████▏ | 23/28 [00:05<00:01,  4.00it/s]\n 86%|████████▌ | 24/28 [00:05<00:01,  3.99it/s]\n 89%|████████▉ | 25/28 [00:06<00:00,  3.99it/s]\n 93%|█████████▎| 26/28 [00:06<00:00,  3.99it/s]\n 96%|█████████▋| 27/28 [00:06<00:00,  3.99it/s]\n100%|██████████| 28/28 [00:06<00:00,  3.99it/s]\n100%|██████████| 28/28 [00:06<00:00,  4.02it/s]\nTotal safe images: 1 out of 1",
  "metrics": {
    "predict_time": 7.249102004,
    "total_time": 7.255479
  },
  "output": [
    "https://replicate.delivery/xezq/8YqNWom5D9ZZLxmYa0SRLwo5m1lZVfZmEa28RVvd1vTo7pGKA/out-0.webp"
  ],
  "started_at": "2025-02-08T16:52:25.690377Z",
  "status": "succeeded",
  "urls": {
    "stream": "https://stream.replicate.com/v1/files/bcwr-mh2x6chm44obbrd5vuzxf5nmxg6ep24wjsr2ezrlxlmkmrdgabxa",
    "get": "https://api.replicate.com/v1/predictions/cz134hgbthrm80cmwsxbq1gvv8",
    "cancel": "https://api.replicate.com/v1/predictions/cz134hgbthrm80cmwsxbq1gvv8/cancel"
  },
  "version": "54cc655616e24a8f59010c48d351ce1192c0581885ffcb839be388309f0a85af"
}

Generated in

7.3 seconds

Tweak it ShareReport

Prediction

cesarvega/my-alinamodel:54cc655616e24a8f59010c48d351ce1192c0581885ffcb839be388309f0a85af

Model

cesarvega/my-alinamodel:54cc6556

bajrcytm11rma0cmwssvjmjt4m

Status

Succeeded

Source

Web

Hardware

H100

Total duration

10.1s

Created

5 months ago

Input

model: dev
prompt: a photo of alina in the beach of Dubai in bathing suit, wide shot
go_fast
lora_scale: 1
megapixels: 1
num_outputs: 1
aspect_ratio: 1:1
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 photo of alina in the beach of Dubai in bathing suit, wide shot",
  "go_fast": false,
  "lora_scale": 1,
  "megapixels": "1",
  "num_outputs": 1,
  "aspect_ratio": "1:1",
  "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 cesarvega/my-alinamodel using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "cesarvega/my-alinamodel:54cc655616e24a8f59010c48d351ce1192c0581885ffcb839be388309f0a85af",
  {
    input: {
      model: "dev",
      prompt: "a photo of alina in the beach of Dubai in bathing suit, wide shot",
      go_fast: false,
      lora_scale: 1,
      megapixels: "1",
      num_outputs: 1,
      aspect_ratio: "1:1",
      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 cesarvega/my-alinamodel using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "cesarvega/my-alinamodel:54cc655616e24a8f59010c48d351ce1192c0581885ffcb839be388309f0a85af",
    input={
        "model": "dev",
        "prompt": "a photo of alina in the beach of Dubai in bathing suit, wide shot",
        "go_fast": False,
        "lora_scale": 1,
        "megapixels": "1",
        "num_outputs": 1,
        "aspect_ratio": "1:1",
        "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 cesarvega/my-alinamodel 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": "cesarvega/my-alinamodel:54cc655616e24a8f59010c48d351ce1192c0581885ffcb839be388309f0a85af",
    "input": {
      "model": "dev",
      "prompt": "a photo of alina in the beach of Dubai in bathing suit, wide shot",
      "go_fast": false,
      "lora_scale": 1,
      "megapixels": "1",
      "num_outputs": 1,
      "aspect_ratio": "1:1",
      "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": "2025-02-08T16:45:15.505119Z",
  "created_at": "2025-02-08T16:45:05.416000Z",
  "data_removed": false,
  "error": null,
  "id": "bajrcytm11rma0cmwssvjmjt4m",
  "input": {
    "model": "dev",
    "prompt": "a photo of alina in the beach of Dubai in bathing suit, wide shot",
    "go_fast": false,
    "lora_scale": 1,
    "megapixels": "1",
    "num_outputs": 1,
    "aspect_ratio": "1:1",
    "output_format": "webp",
    "guidance_scale": 3,
    "output_quality": 80,
    "prompt_strength": 0.8,
    "extra_lora_scale": 1,
    "num_inference_steps": 28
  },
  "logs": "free=28748105641984\nDownloading weights\n2025-02-08T16:45:05Z | INFO  | [ Initiating ] chunk_size=150M dest=/tmp/tmp1ee4m889/weights url=https://replicate.delivery/xezq/NDkfE21qfzlV4kQGGq6siQqzERgXl54cEkh7gLERIH9wpTNUA/trained_model.tar\n2025-02-08T16:45:07Z | INFO  | [ Complete ] dest=/tmp/tmp1ee4m889/weights size=\"172 MB\" total_elapsed=2.253s url=https://replicate.delivery/xezq/NDkfE21qfzlV4kQGGq6siQqzERgXl54cEkh7gLERIH9wpTNUA/trained_model.tar\nDownloaded weights in 2.28s\nLoaded LoRAs in 2.83s\nUsing seed: 33623\nPrompt: a photo of alina in the beach of Dubai in bathing suit, wide shot\n[!] txt2img mode\n  0%|          | 0/28 [00:00<?, ?it/s]\n  4%|▎         | 1/28 [00:00<00:06,  4.06it/s]\n  7%|▋         | 2/28 [00:00<00:05,  4.59it/s]\n 11%|█         | 3/28 [00:00<00:05,  4.32it/s]\n 14%|█▍        | 4/28 [00:00<00:05,  4.20it/s]\n 18%|█▊        | 5/28 [00:01<00:05,  4.14it/s]\n 21%|██▏       | 6/28 [00:01<00:05,  4.11it/s]\n 25%|██▌       | 7/28 [00:01<00:05,  4.08it/s]\n 29%|██▊       | 8/28 [00:01<00:04,  4.06it/s]\n 32%|███▏      | 9/28 [00:02<00:04,  4.05it/s]\n 36%|███▌      | 10/28 [00:02<00:04,  4.04it/s]\n 39%|███▉      | 11/28 [00:02<00:04,  4.04it/s]\n 43%|████▎     | 12/28 [00:02<00:03,  4.03it/s]\n 46%|████▋     | 13/28 [00:03<00:03,  4.03it/s]\n 50%|█████     | 14/28 [00:03<00:03,  4.04it/s]\n 54%|█████▎    | 15/28 [00:03<00:03,  4.03it/s]\n 57%|█████▋    | 16/28 [00:03<00:02,  4.03it/s]\n 61%|██████    | 17/28 [00:04<00:02,  4.03it/s]\n 64%|██████▍   | 18/28 [00:04<00:02,  4.03it/s]\n 68%|██████▊   | 19/28 [00:04<00:02,  4.03it/s]\n 71%|███████▏  | 20/28 [00:04<00:01,  4.03it/s]\n 75%|███████▌  | 21/28 [00:05<00:01,  4.03it/s]\n 79%|███████▊  | 22/28 [00:05<00:01,  4.03it/s]\n 82%|████████▏ | 23/28 [00:05<00:01,  4.03it/s]\n 86%|████████▌ | 24/28 [00:05<00:00,  4.03it/s]\n 89%|████████▉ | 25/28 [00:06<00:00,  4.03it/s]\n 93%|█████████▎| 26/28 [00:06<00:00,  4.03it/s]\n 96%|█████████▋| 27/28 [00:06<00:00,  4.03it/s]\n100%|██████████| 28/28 [00:06<00:00,  4.03it/s]\n100%|██████████| 28/28 [00:06<00:00,  4.06it/s]\nTotal safe images: 1 out of 1",
  "metrics": {
    "predict_time": 10.05671047,
    "total_time": 10.089119
  },
  "output": [
    "https://replicate.delivery/xezq/XSTXQYqeBiz8MykBms8wxEpv3tfMlizM9WV7UmV3wEObwTNUA/out-0.webp"
  ],
  "started_at": "2025-02-08T16:45:05.448408Z",
  "status": "succeeded",
  "urls": {
    "stream": "https://stream.replicate.com/v1/files/bcwr-dwegtu2ognvq6ql5lm4q7jxqpul55t2gubuplyhvc45ofhlfwooa",
    "get": "https://api.replicate.com/v1/predictions/bajrcytm11rma0cmwssvjmjt4m",
    "cancel": "https://api.replicate.com/v1/predictions/bajrcytm11rma0cmwssvjmjt4m/cancel"
  },
  "version": "54cc655616e24a8f59010c48d351ce1192c0581885ffcb839be388309f0a85af"
}

Generated in

10.1 seconds

Tweak it ShareReport

free=28748105641984
Downloading weights
2025-02-08T16:45:05Z | INFO  | [ Initiating ] chunk_size=150M dest=/tmp/tmp1ee4m889/weights url=https://replicate.delivery/xezq/NDkfE21qfzlV4kQGGq6siQqzERgXl54cEkh7gLERIH9wpTNUA/trained_model.tar
2025-02-08T16:45:07Z | INFO  | [ Complete ] dest=/tmp/tmp1ee4m889/weights size="172 MB" total_elapsed=2.253s url=https://replicate.delivery/xezq/NDkfE21qfzlV4kQGGq6siQqzERgXl54cEkh7gLERIH9wpTNUA/trained_model.tar
Downloaded weights in 2.28s
Loaded LoRAs in 2.83s
Using seed: 33623
Prompt: a photo of alina in the beach of Dubai in bathing suit, wide shot
[!] txt2img mode
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100%|██████████| 28/28 [00:06<00:00,  4.06it/s]
Total safe images: 1 out of 1

Prediction

cesarvega/my-alinamodel:54cc655616e24a8f59010c48d351ce1192c0581885ffcb839be388309f0a85af

Model

cesarvega/my-alinamodel:54cc6556

mh2ze95nsdrm80cmwv3r5f9fc4

Status

Succeeded

Source

Web

Hardware

H100

Total duration

7.8s

Created

5 months ago

Input

model: dev
prompt: a photo of alina dancing
go_fast
lora_scale: 1
megapixels: 1
num_outputs: 1
aspect_ratio: 1:1
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 photo of alina  dancing",
  "go_fast": false,
  "lora_scale": 1,
  "megapixels": "1",
  "num_outputs": 1,
  "aspect_ratio": "1:1",
  "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 cesarvega/my-alinamodel using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "cesarvega/my-alinamodel:54cc655616e24a8f59010c48d351ce1192c0581885ffcb839be388309f0a85af",
  {
    input: {
      model: "dev",
      prompt: "a photo of alina  dancing",
      go_fast: false,
      lora_scale: 1,
      megapixels: "1",
      num_outputs: 1,
      aspect_ratio: "1:1",
      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 cesarvega/my-alinamodel using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "cesarvega/my-alinamodel:54cc655616e24a8f59010c48d351ce1192c0581885ffcb839be388309f0a85af",
    input={
        "model": "dev",
        "prompt": "a photo of alina  dancing",
        "go_fast": False,
        "lora_scale": 1,
        "megapixels": "1",
        "num_outputs": 1,
        "aspect_ratio": "1:1",
        "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 cesarvega/my-alinamodel 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": "cesarvega/my-alinamodel:54cc655616e24a8f59010c48d351ce1192c0581885ffcb839be388309f0a85af",
    "input": {
      "model": "dev",
      "prompt": "a photo of alina  dancing",
      "go_fast": false,
      "lora_scale": 1,
      "megapixels": "1",
      "num_outputs": 1,
      "aspect_ratio": "1:1",
      "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": "2025-02-08T18:17:23.254753Z",
  "created_at": "2025-02-08T18:17:15.467000Z",
  "data_removed": false,
  "error": null,
  "id": "mh2ze95nsdrm80cmwv3r5f9fc4",
  "input": {
    "model": "dev",
    "prompt": "a photo of alina  dancing",
    "go_fast": false,
    "lora_scale": 1,
    "megapixels": "1",
    "num_outputs": 1,
    "aspect_ratio": "1:1",
    "output_format": "webp",
    "guidance_scale": 3,
    "output_quality": 80,
    "prompt_strength": 0.8,
    "extra_lora_scale": 1,
    "num_inference_steps": 28
  },
  "logs": "Loaded LoRAs in 0.56s\nUsing seed: 24661\nPrompt: a photo of alina  dancing\n[!] txt2img mode\n  0%|          | 0/28 [00:00<?, ?it/s]\n  4%|▎         | 1/28 [00:00<00:06,  4.01it/s]\n  7%|▋         | 2/28 [00:00<00:05,  4.53it/s]\n 11%|█         | 3/28 [00:00<00:05,  4.28it/s]\n 14%|█▍        | 4/28 [00:00<00:05,  4.17it/s]\n 18%|█▊        | 5/28 [00:01<00:05,  4.11it/s]\n 21%|██▏       | 6/28 [00:01<00:05,  4.07it/s]\n 25%|██▌       | 7/28 [00:01<00:05,  4.04it/s]\n 29%|██▊       | 8/28 [00:01<00:04,  4.03it/s]\n 32%|███▏      | 9/28 [00:02<00:04,  4.02it/s]\n 36%|███▌      | 10/28 [00:02<00:04,  4.02it/s]\n 39%|███▉      | 11/28 [00:02<00:04,  4.01it/s]\n 43%|████▎     | 12/28 [00:02<00:03,  4.01it/s]\n 46%|████▋     | 13/28 [00:03<00:03,  4.00it/s]\n 50%|█████     | 14/28 [00:03<00:03,  3.99it/s]\n 54%|█████▎    | 15/28 [00:03<00:03,  3.99it/s]\n 57%|█████▋    | 16/28 [00:03<00:03,  3.98it/s]\n 61%|██████    | 17/28 [00:04<00:02,  3.99it/s]\n 64%|██████▍   | 18/28 [00:04<00:02,  3.99it/s]\n 68%|██████▊   | 19/28 [00:04<00:02,  4.00it/s]\n 71%|███████▏  | 20/28 [00:04<00:01,  4.00it/s]\n 75%|███████▌  | 21/28 [00:05<00:01,  4.00it/s]\n 79%|███████▊  | 22/28 [00:05<00:01,  4.00it/s]\n 82%|████████▏ | 23/28 [00:05<00:01,  3.99it/s]\n 86%|████████▌ | 24/28 [00:05<00:01,  4.00it/s]\n 89%|████████▉ | 25/28 [00:06<00:00,  4.00it/s]\n 93%|█████████▎| 26/28 [00:06<00:00,  3.99it/s]\n 96%|█████████▋| 27/28 [00:06<00:00,  3.99it/s]\n100%|██████████| 28/28 [00:06<00:00,  3.99it/s]\n100%|██████████| 28/28 [00:06<00:00,  4.02it/s]\nTotal safe images: 1 out of 1",
  "metrics": {
    "predict_time": 7.781390335,
    "total_time": 7.787753
  },
  "output": [
    "https://replicate.delivery/xezq/9WYvxslIOmp6MJ17uidRUqMq1TYzKufTpNe2Ko14VkMzGVNUA/out-0.webp"
  ],
  "started_at": "2025-02-08T18:17:15.473363Z",
  "status": "succeeded",
  "urls": {
    "stream": "https://stream.replicate.com/v1/files/bcwr-vkxhfng4gspitqnzylfffdwhmfbuof5hq7xxwowbu26nabgmbpua",
    "get": "https://api.replicate.com/v1/predictions/mh2ze95nsdrm80cmwv3r5f9fc4",
    "cancel": "https://api.replicate.com/v1/predictions/mh2ze95nsdrm80cmwv3r5f9fc4/cancel"
  },
  "version": "54cc655616e24a8f59010c48d351ce1192c0581885ffcb839be388309f0a85af"
}

Generated in

7.8 seconds

Tweak it ShareReport