Prediction

Model

jonathan-hubjam/red-vase:319dfef6

41g9chabqdrmc0ckwf6tkftnv8

Status

Succeeded

Source

Web

Hardware

H100

Total duration

8.0s

Created

12 months ago

Webhook

–

Input

prompt: RDVSE33 red and grey vase with thin neck on a shelf
aspect_ratio: 1:1
prompt_strength: 0.8
model: dev
num_outputs: 1
num_inference_steps: 28
guidance_scale: 3
output_format: webp
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": "webp",
  "output_quality": 80,
  "prompt": "RDVSE33 red and grey vase with thin neck on a shelf",
  "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_8NK**********************************

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 jonathan-hubjam/red-vase using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "jonathan-hubjam/red-vase:319dfef6fae7a77f925a55007abddb7b052903e263eba1d19df723cb285c7217",
  {
    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: "webp",
      output_quality: 80,
      prompt: "RDVSE33 red and grey vase with thin neck on a shelf",
      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_8NK**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

Run jonathan-hubjam/red-vase using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "jonathan-hubjam/red-vase:319dfef6fae7a77f925a55007abddb7b052903e263eba1d19df723cb285c7217",
    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": "webp",
        "output_quality": 80,
        "prompt": "RDVSE33 red and grey vase with thin neck on a shelf",
        "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_8NK**********************************

This is your API token. Keep it to yourself.

Run jonathan-hubjam/red-vase 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": "jonathan-hubjam/red-vase:319dfef6fae7a77f925a55007abddb7b052903e263eba1d19df723cb285c7217",
    "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": "webp",
      "output_quality": 80,
      "prompt": "RDVSE33 red and grey vase with thin neck on a shelf",
      "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": "41g9chabqdrmc0ckwf6tkftnv8",
  "model": "jonathan-hubjam/red-vase",
  "version": "319dfef6fae7a77f925a55007abddb7b052903e263eba1d19df723cb285c7217",
  "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": "webp",
    "output_quality": 80,
    "prompt": "RDVSE33 red and grey vase with thin neck on a shelf",
    "prompt_strength": 0.8
  },
  "logs": "2024-12-20 11:21:42.642 | DEBUG    | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2024-12-20 11:21:42.643 | DEBUG    | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA:   0%|          | 0/304 [00:00<?, ?it/s]\nApplying LoRA:  92%|█████████▏| 281/304 [00:00<00:00, 2806.40it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2721.48it/s]\n2024-12-20 11:21:42.755 | SUCCESS  | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s\nfree=29200220561408\nDownloading weights\n2024-12-20T11:21:42Z | INFO  | [ Initiating ] chunk_size=150M dest=/tmp/tmp0ud1w4wl/weights url=https://replicate.delivery/xezq/9hspEtJeMzTyfEcLM1qEaEHZHxR82A8bSmnLdcfohd61XK4nA/trained_model.tar\n2024-12-20T11:21:44Z | INFO  | [ Complete ] dest=/tmp/tmp0ud1w4wl/weights size=\"172 MB\" total_elapsed=1.494s url=https://replicate.delivery/xezq/9hspEtJeMzTyfEcLM1qEaEHZHxR82A8bSmnLdcfohd61XK4nA/trained_model.tar\nDownloaded weights in 1.52s\n2024-12-20 11:21:44.275 | INFO     | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/4b0fb6b46b5d97f1\n2024-12-20 11:21:44.346 | INFO     | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2024-12-20 11:21:44.346 | DEBUG    | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2024-12-20 11:21:44.346 | 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, 2809.73it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2725.85it/s]\n2024-12-20 11:21:44.458 | SUCCESS  | fp8.lora_loading:load_lora:539 - LoRA applied in 0.18s\nUsing seed: 1041\n0it [00:00, ?it/s]\n1it [00:00,  8.36it/s]\n2it [00:00,  5.86it/s]\n3it [00:00,  5.34it/s]\n4it [00:00,  5.13it/s]\n5it [00:00,  5.00it/s]\n6it [00:01,  4.93it/s]\n7it [00:01,  4.88it/s]\n8it [00:01,  4.86it/s]\n9it [00:01,  4.85it/s]\n10it [00:01,  4.84it/s]\n11it [00:02,  4.83it/s]\n12it [00:02,  4.81it/s]\n13it [00:02,  4.80it/s]\n14it [00:02,  4.81it/s]\n15it [00:03,  4.79it/s]\n16it [00:03,  4.79it/s]\n17it [00:03,  4.80it/s]\n18it [00:03,  4.80it/s]\n19it [00:03,  4.81it/s]\n20it [00:04,  4.80it/s]\n21it [00:04,  4.80it/s]\n22it [00:04,  4.79it/s]\n23it [00:04,  4.79it/s]\n24it [00:04,  4.80it/s]\n25it [00:05,  4.81it/s]\n26it [00:05,  4.81it/s]\n27it [00:05,  4.80it/s]\n28it [00:05,  4.78it/s]\n28it [00:05,  4.87it/s]\nTotal safe images: 1 out of 1",
  "output": [
    "https://replicate.delivery/xezq/m2pfuq5DTUwzTihw1Ityuyx1mrkStHsUPqTqWEIS4wfOVw8TA/out-0.webp"
  ],
  "data_removed": false,
  "error": null,
  "source": "web",
  "status": "succeeded",
  "created_at": "2024-12-20T11:21:42.587Z",
  "started_at": "2024-12-20T11:21:42.643465Z",
  "completed_at": "2024-12-20T11:21:50.558515Z",
  "urls": {
    "cancel": "https://api.replicate.com/v1/predictions/41g9chabqdrmc0ckwf6tkftnv8/cancel",
    "get": "https://api.replicate.com/v1/predictions/41g9chabqdrmc0ckwf6tkftnv8",
    "stream": "https://stream.replicate.com/v1/files/bcwr-efmvx2cn6gebkv42fyh3xty6pxe6z7plvnzo6a7kpkjadnffgpgq",
    "web": "https://replicate.com/p/41g9chabqdrmc0ckwf6tkftnv8"
  },
  "metrics": {
    "predict_time": 7.91505011,
    "total_time": 7.971515
  }
}

Generated in

7.9 seconds

Tweak it Report

2024-12-20 11:21:42.642 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2024-12-20 11:21:42.643 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 92%|█████████▏| 281/304 [00:00<00:00, 2806.40it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2721.48it/s] 2024-12-20 11:21:42.755 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s free=29200220561408 Downloading weights 2024-12-20T11:21:42Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp0ud1w4wl/weights url=https://replicate.delivery/xezq/9hspEtJeMzTyfEcLM1qEaEHZHxR82A8bSmnLdcfohd61XK4nA/trained_model.tar 2024-12-20T11:21:44Z | INFO | [ Complete ] dest=/tmp/tmp0ud1w4wl/weights size="172 MB" total_elapsed=1.494s url=https://replicate.delivery/xezq/9hspEtJeMzTyfEcLM1qEaEHZHxR82A8bSmnLdcfohd61XK4nA/trained_model.tar Downloaded weights in 1.52s 2024-12-20 11:21:44.275 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/4b0fb6b46b5d97f1 2024-12-20 11:21:44.346 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2024-12-20 11:21:44.346 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2024-12-20 11:21:44.346 | 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, 2809.73it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2725.85it/s] 2024-12-20 11:21:44.458 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.18s Using seed: 1041 0it [00:00, ?it/s] 1it [00:00, 8.36it/s] 2it [00:00, 5.86it/s] 3it [00:00, 5.34it/s] 4it [00:00, 5.13it/s] 5it [00:00, 5.00it/s] 6it [00:01, 4.93it/s] 7it [00:01, 4.88it/s] 8it [00:01, 4.86it/s] 9it [00:01, 4.85it/s] 10it [00:01, 4.84it/s] 11it [00:02, 4.83it/s] 12it [00:02, 4.81it/s] 13it [00:02, 4.80it/s] 14it [00:02, 4.81it/s] 15it [00:03, 4.79it/s] 16it [00:03, 4.79it/s] 17it [00:03, 4.80it/s] 18it [00:03, 4.80it/s] 19it [00:03, 4.81it/s] 20it [00:04, 4.80it/s] 21it [00:04, 4.80it/s] 22it [00:04, 4.79it/s] 23it [00:04, 4.79it/s] 24it [00:04, 4.80it/s] 25it [00:05, 4.81it/s] 26it [00:05, 4.81it/s] 27it [00:05, 4.80it/s] 28it [00:05, 4.78it/s] 28it [00:05, 4.87it/s] Total safe images: 1 out of 1