astelvida / genmoji-gen

{
  "model": "dev",
  "prompt": "GENMOJI , emoji of a girl eating a pumpkin",
  "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 astelvida/genmoji-gen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "astelvida/genmoji-gen:a72b26a6ff81284aca4f889cf47f8dd6ca6aafc46901c95afb38141db9f9183c",
  {
    input: {
      model: "dev",
      prompt: "GENMOJI , emoji of a girl eating a pumpkin",
      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 astelvida/genmoji-gen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "astelvida/genmoji-gen:a72b26a6ff81284aca4f889cf47f8dd6ca6aafc46901c95afb38141db9f9183c",
    input={
        "model": "dev",
        "prompt": "GENMOJI , emoji of a girl eating a pumpkin",
        "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 astelvida/genmoji-gen 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": "astelvida/genmoji-gen:a72b26a6ff81284aca4f889cf47f8dd6ca6aafc46901c95afb38141db9f9183c",
    "input": {
      "model": "dev",
      "prompt": "GENMOJI , emoji of a girl eating a pumpkin",
      "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": "2025-01-13T02:42:57.594624Z",
  "created_at": "2025-01-13T02:42:47.175000Z",
  "data_removed": false,
  "error": null,
  "id": "xf8saw6n0xrma0cmbp5b62yj5c",
  "input": {
    "model": "dev",
    "prompt": "GENMOJI , emoji of a girl eating a pumpkin",
    "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": "2025-01-13 02:42:49.255 | DEBUG    | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-13 02:42:49.256 | DEBUG    | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA:   0%|          | 0/304 [00:00<?, ?it/s]\nApplying LoRA:  93%|█████████▎| 282/304 [00:00<00:00, 2803.01it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2678.28it/s]\n2025-01-13 02:42:49.370 | SUCCESS  | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s\nfree=29227847204864\nDownloading weights\n2025-01-13T02:42:49Z | INFO  | [ Initiating ] chunk_size=150M dest=/tmp/tmpoxnwxjau/weights url=https://replicate.delivery/xezq/QWqxm2x5YgK0PZKGfzvVL8wCvHTyaqB1Ue25pgl94qxV4iEUA/trained_model.tar\n2025-01-13T02:42:51Z | INFO  | [ Complete ] dest=/tmp/tmpoxnwxjau/weights size=\"172 MB\" total_elapsed=1.928s url=https://replicate.delivery/xezq/QWqxm2x5YgK0PZKGfzvVL8wCvHTyaqB1Ue25pgl94qxV4iEUA/trained_model.tar\nDownloaded weights in 1.95s\n2025-01-13 02:42:51.324 | INFO     | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/a47eb634a5b0e427\n2025-01-13 02:42:51.395 | INFO     | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2025-01-13 02:42:51.396 | DEBUG    | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-13 02:42:51.396 | DEBUG    | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA:   0%|          | 0/304 [00:00<?, ?it/s]\nApplying LoRA:  93%|█████████▎| 282/304 [00:00<00:00, 2804.62it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2679.59it/s]\n2025-01-13 02:42:51.510 | SUCCESS  | fp8.lora_loading:load_lora:539 - LoRA applied in 0.19s\nUsing seed: 48331\n0it [00:00, ?it/s]\n1it [00:00,  8.34it/s]\n2it [00:00,  5.85it/s]\n3it [00:00,  5.33it/s]\n4it [00:00,  5.12it/s]\n5it [00:00,  5.01it/s]\n6it [00:01,  4.93it/s]\n7it [00:01,  4.89it/s]\n8it [00:01,  4.87it/s]\n9it [00:01,  4.86it/s]\n10it [00:01,  4.84it/s]\n11it [00:02,  4.83it/s]\n12it [00:02,  4.83it/s]\n13it [00:02,  4.82it/s]\n14it [00:02,  4.82it/s]\n15it [00:03,  4.82it/s]\n16it [00:03,  4.82it/s]\n17it [00:03,  4.82it/s]\n18it [00:03,  4.82it/s]\n19it [00:03,  4.81it/s]\n20it [00:04,  4.82it/s]\n21it [00:04,  4.82it/s]\n22it [00:04,  4.82it/s]\n23it [00:04,  4.82it/s]\n24it [00:04,  4.81it/s]\n25it [00:05,  4.81it/s]\n26it [00:05,  4.81it/s]\n27it [00:05,  4.81it/s]\n28it [00:05,  4.82it/s]\n28it [00:05,  4.89it/s]\nTotal safe images: 1 out of 1",
  "metrics": {
    "predict_time": 8.337822605,
    "total_time": 10.419624
  },
  "output": [
    "https://replicate.delivery/xezq/XK6TngG04aqjPte1q7pfTgf2bo0w1803JKQRVRnVbc2i9FJoA/out-0.webp"
  ],
  "started_at": "2025-01-13T02:42:49.256802Z",
  "status": "succeeded",
  "urls": {
    "stream": "https://stream.replicate.com/v1/files/bcwr-oqfan2vmpak4kqkyssvilszcyl6okc3wf56mba2fly4gqm4p56ha",
    "get": "https://api.replicate.com/v1/predictions/xf8saw6n0xrma0cmbp5b62yj5c",
    "cancel": "https://api.replicate.com/v1/predictions/xf8saw6n0xrma0cmbp5b62yj5c/cancel"
  },
  "version": "a72b26a6ff81284aca4f889cf47f8dd6ca6aafc46901c95afb38141db9f9183c"
}

Generated in

8.3 seconds

Tweak it ShareReport

2025-01-13 02:42:49.255 | DEBUG    | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2025-01-13 02:42:49.256 | DEBUG    | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA:   0%|          | 0/304 [00:00<?, ?it/s]
Applying LoRA:  93%|█████████▎| 282/304 [00:00<00:00, 2803.01it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2678.28it/s]
2025-01-13 02:42:49.370 | SUCCESS  | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s
free=29227847204864
Downloading weights
2025-01-13T02:42:49Z | INFO  | [ Initiating ] chunk_size=150M dest=/tmp/tmpoxnwxjau/weights url=https://replicate.delivery/xezq/QWqxm2x5YgK0PZKGfzvVL8wCvHTyaqB1Ue25pgl94qxV4iEUA/trained_model.tar
2025-01-13T02:42:51Z | INFO  | [ Complete ] dest=/tmp/tmpoxnwxjau/weights size="172 MB" total_elapsed=1.928s url=https://replicate.delivery/xezq/QWqxm2x5YgK0PZKGfzvVL8wCvHTyaqB1Ue25pgl94qxV4iEUA/trained_model.tar
Downloaded weights in 1.95s
2025-01-13 02:42:51.324 | INFO     | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/a47eb634a5b0e427
2025-01-13 02:42:51.395 | INFO     | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded
2025-01-13 02:42:51.396 | DEBUG    | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2025-01-13 02:42:51.396 | DEBUG    | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA:   0%|          | 0/304 [00:00<?, ?it/s]
Applying LoRA:  93%|█████████▎| 282/304 [00:00<00:00, 2804.62it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2679.59it/s]
2025-01-13 02:42:51.510 | SUCCESS  | fp8.lora_loading:load_lora:539 - LoRA applied in 0.19s
Using seed: 48331
0it [00:00, ?it/s]
1it [00:00,  8.34it/s]
2it [00:00,  5.85it/s]
3it [00:00,  5.33it/s]
4it [00:00,  5.12it/s]
5it [00:00,  5.01it/s]
6it [00:01,  4.93it/s]
7it [00:01,  4.89it/s]
8it [00:01,  4.87it/s]
9it [00:01,  4.86it/s]
10it [00:01,  4.84it/s]
11it [00:02,  4.83it/s]
12it [00:02,  4.83it/s]
13it [00:02,  4.82it/s]
14it [00:02,  4.82it/s]
15it [00:03,  4.82it/s]
16it [00:03,  4.82it/s]
17it [00:03,  4.82it/s]
18it [00:03,  4.82it/s]
19it [00:03,  4.81it/s]
20it [00:04,  4.82it/s]
21it [00:04,  4.82it/s]
22it [00:04,  4.82it/s]
23it [00:04,  4.82it/s]
24it [00:04,  4.81it/s]
25it [00:05,  4.81it/s]
26it [00:05,  4.81it/s]
27it [00:05,  4.81it/s]
28it [00:05,  4.82it/s]
28it [00:05,  4.89it/s]
Total safe images: 1 out of 1

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