Prediction

Model

andrei907/andre:91c7f8f5

q5c8jzeyvnrme0cmey08acbegr

Status

Succeeded

Source

Web

Hardware

H100

Total duration

7.8s

Created

11 months ago

Webhook

–

Input

prompt: andre înconjurat de cascade care curg în gol, peisaj de fantezie uluitor
aspect_ratio: 1:1
prompt_strength: 0.8
model: dev
num_outputs: 1
num_inference_steps: 28
guidance_scale: 3
output_format: jpg
output_quality: 80
go_fast: false
megapixels: 1
lora_scale: 1
extra_lora_scale: 1

{
  "aspect_ratio": "1:1",
  "extra_lora_scale": 1,
  "go_fast": false,
  "guidance_scale": 3,
  "lora_scale": 1,
  "megapixels": "1",
  "model": "dev",
  "num_inference_steps": 28,
  "num_outputs": 1,
  "output_format": "jpg",
  "output_quality": 80,
  "prompt": "andre înconjurat de cascade care curg în gol, peisaj de fantezie uluitor",
  "prompt_strength": 0.8
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_caj**********************************

This is your API token. Keep it to yourself.

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 andrei907/andre using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "andrei907/andre:91c7f8f5d910f169d295cdc12d9dfcc6ead290e93b3172a9e70dcc6b20910e50",
  {
    input: {
      aspect_ratio: "1:1",
      extra_lora_scale: 1,
      go_fast: false,
      guidance_scale: 3,
      lora_scale: 1,
      megapixels: "1",
      model: "dev",
      num_inference_steps: 28,
      num_outputs: 1,
      output_format: "jpg",
      output_quality: 80,
      prompt: "andre înconjurat de cascade care curg în gol, peisaj de fantezie uluitor",
      prompt_strength: 0.8
    }
  }
);

// 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=r8_caj**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

Run andrei907/andre using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "andrei907/andre:91c7f8f5d910f169d295cdc12d9dfcc6ead290e93b3172a9e70dcc6b20910e50",
    input={
        "aspect_ratio": "1:1",
        "extra_lora_scale": 1,
        "go_fast": False,
        "guidance_scale": 3,
        "lora_scale": 1,
        "megapixels": "1",
        "model": "dev",
        "num_inference_steps": 28,
        "num_outputs": 1,
        "output_format": "jpg",
        "output_quality": 80,
        "prompt": "andre înconjurat de cascade care curg în gol, peisaj de fantezie uluitor",
        "prompt_strength": 0.8
    }
)

# 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=r8_caj**********************************

This is your API token. Keep it to yourself.

Run andrei907/andre 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": "andrei907/andre:91c7f8f5d910f169d295cdc12d9dfcc6ead290e93b3172a9e70dcc6b20910e50",
    "input": {
      "aspect_ratio": "1:1",
      "extra_lora_scale": 1,
      "go_fast": false,
      "guidance_scale": 3,
      "lora_scale": 1,
      "megapixels": "1",
      "model": "dev",
      "num_inference_steps": 28,
      "num_outputs": 1,
      "output_format": "jpg",
      "output_quality": 80,
      "prompt": "andre înconjurat de cascade care curg în gol, peisaj de fantezie uluitor",
      "prompt_strength": 0.8
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "id": "q5c8jzeyvnrme0cmey08acbegr",
  "model": "andrei907/andre",
  "version": "91c7f8f5d910f169d295cdc12d9dfcc6ead290e93b3172a9e70dcc6b20910e50",
  "input": {
    "aspect_ratio": "1:1",
    "extra_lora_scale": 1,
    "go_fast": false,
    "guidance_scale": 3,
    "lora_scale": 1,
    "megapixels": "1",
    "model": "dev",
    "num_inference_steps": 28,
    "num_outputs": 1,
    "output_format": "jpg",
    "output_quality": 80,
    "prompt": "andre înconjurat de cascade care curg în gol, peisaj de fantezie uluitor",
    "prompt_strength": 0.8
  },
  "logs": "2025-01-18 03:42:03.181 | DEBUG    | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-18 03:42:03.182 | DEBUG    | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA:   0%|          | 0/304 [00:00<?, ?it/s]\nApplying LoRA:  90%|████████▉ | 273/304 [00:00<00:00, 2721.90it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2653.06it/s]\n2025-01-18 03:42:03.297 | SUCCESS  | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.12s\n2025-01-18 03:42:03.298 | INFO     | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/5b32327e723ba22f\n2025-01-18 03:42:03.414 | INFO     | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2025-01-18 03:42:03.414 | DEBUG    | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-18 03:42:03.414 | DEBUG    | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA:   0%|          | 0/304 [00:00<?, ?it/s]\nApplying LoRA:  90%|████████▉ | 273/304 [00:00<00:00, 2723.24it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2653.56it/s]\n2025-01-18 03:42:03.529 | SUCCESS  | fp8.lora_loading:load_lora:539 - LoRA applied in 0.23s\nUsing seed: 22898\n0it [00:00, ?it/s]\n1it [00:00,  8.33it/s]\n2it [00:00,  5.80it/s]\n3it [00:00,  5.28it/s]\n4it [00:00,  5.07it/s]\n5it [00:00,  4.91it/s]\n6it [00:01,  4.81it/s]\n7it [00:01,  4.77it/s]\n8it [00:01,  4.76it/s]\n9it [00:01,  4.75it/s]\n10it [00:02,  4.71it/s]\n11it [00:02,  4.70it/s]\n12it [00:02,  4.71it/s]\n13it [00:02,  4.71it/s]\n14it [00:02,  4.71it/s]\n15it [00:03,  4.69it/s]\n16it [00:03,  4.67it/s]\n17it [00:03,  4.69it/s]\n18it [00:03,  4.70it/s]\n19it [00:03,  4.70it/s]\n20it [00:04,  4.68it/s]\n21it [00:04,  4.68it/s]\n22it [00:04,  4.68it/s]\n23it [00:04,  4.69it/s]\n24it [00:05,  4.70it/s]\n25it [00:05,  4.69it/s]\n26it [00:05,  4.69it/s]\n27it [00:05,  4.71it/s]\n28it [00:05,  4.72it/s]\n28it [00:05,  4.78it/s]\nTotal safe images: 1 out of 1",
  "output": [
    "https://replicate.delivery/xezq/pGvzlU4W7r4PMdQauVyTfedbxUpxmNIo0goAcKUEWdURUNGUA/out-0.jpg"
  ],
  "data_removed": false,
  "error": null,
  "source": "web",
  "status": "succeeded",
  "created_at": "2025-01-18T03:42:01.949Z",
  "started_at": "2025-01-18T03:42:03.182842Z",
  "completed_at": "2025-01-18T03:42:09.69223Z",
  "urls": {
    "cancel": "https://api.replicate.com/v1/predictions/q5c8jzeyvnrme0cmey08acbegr/cancel",
    "get": "https://api.replicate.com/v1/predictions/q5c8jzeyvnrme0cmey08acbegr",
    "stream": "https://stream.replicate.com/v1/files/bcwr-auanrsobdilal7imeolfweim25fiqlfx63uhegsvwz4xzszxl5mq",
    "web": "https://replicate.com/p/q5c8jzeyvnrme0cmey08acbegr"
  },
  "metrics": {
    "predict_time": 6.509387928,
    "total_time": 7.74323
  }
}

Generated in

6.5 seconds

Tweak it Report

2025-01-18 03:42:03.181 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-18 03:42:03.182 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 90%|████████▉ | 273/304 [00:00<00:00, 2721.90it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2653.06it/s] 2025-01-18 03:42:03.297 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.12s 2025-01-18 03:42:03.298 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/5b32327e723ba22f 2025-01-18 03:42:03.414 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2025-01-18 03:42:03.414 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-18 03:42:03.414 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 90%|████████▉ | 273/304 [00:00<00:00, 2723.24it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2653.56it/s] 2025-01-18 03:42:03.529 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.23s Using seed: 22898 0it [00:00, ?it/s] 1it [00:00, 8.33it/s] 2it [00:00, 5.80it/s] 3it [00:00, 5.28it/s] 4it [00:00, 5.07it/s] 5it [00:00, 4.91it/s] 6it [00:01, 4.81it/s] 7it [00:01, 4.77it/s] 8it [00:01, 4.76it/s] 9it [00:01, 4.75it/s] 10it [00:02, 4.71it/s] 11it [00:02, 4.70it/s] 12it [00:02, 4.71it/s] 13it [00:02, 4.71it/s] 14it [00:02, 4.71it/s] 15it [00:03, 4.69it/s] 16it [00:03, 4.67it/s] 17it [00:03, 4.69it/s] 18it [00:03, 4.70it/s] 19it [00:03, 4.70it/s] 20it [00:04, 4.68it/s] 21it [00:04, 4.68it/s] 22it [00:04, 4.68it/s] 23it [00:04, 4.69it/s] 24it [00:05, 4.70it/s] 25it [00:05, 4.69it/s] 26it [00:05, 4.69it/s] 27it [00:05, 4.71it/s] 28it [00:05, 4.72it/s] 28it [00:05, 4.78it/s] Total safe images: 1 out of 1