Prediction
sundai-club/alolan_vulpix_flux:c87f3f18ba2909071edc1cfe8012f0df04b05177a1ef0db05572ca52576faaf4ID
h2dqngwz41rme0cmgnxawbc0xr
Status
Succeeded
Source
Web
Hardware
H100
Total duration
Created
Input
- model
- dev
- prompt
- Alolan VULPIX pulling a snow sled to deliver presents to Elsa's castle!
- 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": "Alolan VULPIX pulling a snow sled to deliver presents to Elsa's castle!",
"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 replicateSet the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
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 sundai-club/alolan_vulpix_flux using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"sundai-club/alolan_vulpix_flux:c87f3f18ba2909071edc1cfe8012f0df04b05177a1ef0db05572ca52576faaf4",
{
input: {
model: "dev",
prompt: "Alolan VULPIX pulling a snow sled to deliver presents to Elsa's castle!",
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 replicateSet the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:
import replicateRun sundai-club/alolan_vulpix_flux using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"sundai-club/alolan_vulpix_flux:c87f3f18ba2909071edc1cfe8012f0df04b05177a1ef0db05572ca52576faaf4",
input={
"model": "dev",
"prompt": "Alolan VULPIX pulling a snow sled to deliver presents to Elsa's castle!",
"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
}
)
print(output)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=<paste-your-token-here>Find your API token in your account settings.
Run sundai-club/alolan_vulpix_flux 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": "sundai-club/alolan_vulpix_flux:c87f3f18ba2909071edc1cfe8012f0df04b05177a1ef0db05572ca52576faaf4",
"input": {
"model": "dev",
"prompt": "Alolan VULPIX pulling a snow sled to deliver presents to Elsa\'s castle!",
"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/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:
brew install cogIf you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/sundai-club/alolan_vulpix_flux@sha256:c87f3f18ba2909071edc1cfe8012f0df04b05177a1ef0db05572ca52576faaf4 \
-i 'model="dev"' \
-i $'prompt="Alolan VULPIX pulling a snow sled to deliver presents to Elsa\'s castle!"' \
-i 'go_fast=false' \
-i 'lora_scale=1' \
-i 'megapixels="1"' \
-i 'num_outputs=1' \
-i 'aspect_ratio="1:1"' \
-i 'output_format="webp"' \
-i 'guidance_scale=3' \
-i 'output_quality=80' \
-i 'prompt_strength=0.8' \
-i 'extra_lora_scale=1' \
-i 'num_inference_steps=28'To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/sundai-club/alolan_vulpix_flux@sha256:c87f3f18ba2909071edc1cfe8012f0df04b05177a1ef0db05572ca52576faaf4curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "model": "dev", "prompt": "Alolan VULPIX pulling a snow sled to deliver presents to Elsa\'s castle!", "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 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Output
{
"completed_at": "2025-01-20T20:50:01.850749Z",
"created_at": "2025-01-20T20:49:53.440000Z",
"data_removed": false,
"error": null,
"id": "h2dqngwz41rme0cmgnxawbc0xr",
"input": {
"model": "dev",
"prompt": "Alolan VULPIX pulling a snow sled to deliver presents to Elsa's castle!",
"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": "2025-01-20 20:49:53.700 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-20 20:49:53.700 | 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, 2804.75it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2729.34it/s]\n2025-01-20 20:49:53.812 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s\nfree=29878800396288\nDownloading weights\n2025-01-20T20:49:53Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpfdhiihyh/weights url=https://replicate.delivery/xezq/ib77EhCvApL5CRmZgaPS8iZR3DuT2UZgJxDRpPSrb8ZufiDKA/trained_model.tar\n2025-01-20T20:49:55Z | INFO | [ Complete ] dest=/tmp/tmpfdhiihyh/weights size=\"172 MB\" total_elapsed=1.797s url=https://replicate.delivery/xezq/ib77EhCvApL5CRmZgaPS8iZR3DuT2UZgJxDRpPSrb8ZufiDKA/trained_model.tar\nDownloaded weights in 1.82s\n2025-01-20 20:49:55.636 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/f5a1b7cbc556f6f1\n2025-01-20 20:49:55.706 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2025-01-20 20:49:55.706 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-20 20:49:55.707 | 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, 2809.63it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2734.23it/s]\n2025-01-20 20:49:55.818 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.18s\nUsing seed: 50611\n0it [00:00, ?it/s]\n1it [00:00, 8.43it/s]\n2it [00:00, 5.91it/s]\n3it [00:00, 5.39it/s]\n4it [00:00, 5.18it/s]\n5it [00:00, 5.06it/s]\n6it [00:01, 4.99it/s]\n7it [00:01, 4.95it/s]\n8it [00:01, 4.93it/s]\n9it [00:01, 4.91it/s]\n10it [00:01, 4.90it/s]\n11it [00:02, 4.89it/s]\n12it [00:02, 4.87it/s]\n13it [00:02, 4.87it/s]\n14it [00:02, 4.87it/s]\n15it [00:02, 4.87it/s]\n16it [00:03, 4.87it/s]\n17it [00:03, 4.87it/s]\n18it [00:03, 4.86it/s]\n19it [00:03, 4.86it/s]\n20it [00:04, 4.86it/s]\n21it [00:04, 4.86it/s]\n22it [00:04, 4.86it/s]\n23it [00:04, 4.86it/s]\n24it [00:04, 4.86it/s]\n25it [00:05, 4.87it/s]\n26it [00:05, 4.86it/s]\n27it [00:05, 4.86it/s]\n28it [00:05, 4.86it/s]\n28it [00:05, 4.94it/s]\nTotal safe images: 1 out of 1",
"metrics": {
"predict_time": 8.149572686,
"total_time": 8.410749
},
"output": [
"https://replicate.delivery/xezq/4aUNHy3Ae9XcAC3xVIb7ZfvJXMLGU7uEfRR7eeAi17fe8RjDKA/out-0.webp"
],
"started_at": "2025-01-20T20:49:53.701176Z",
"status": "succeeded",
"urls": {
"stream": "https://stream.replicate.com/v1/files/bcwr-prdei7bi43u3e6udklryhdwpbyz3pjgj3ugryvw5xvqmltj5qrxa",
"get": "https://api.replicate.com/v1/predictions/h2dqngwz41rme0cmgnxawbc0xr",
"cancel": "https://api.replicate.com/v1/predictions/h2dqngwz41rme0cmgnxawbc0xr/cancel"
},
"version": "c87f3f18ba2909071edc1cfe8012f0df04b05177a1ef0db05572ca52576faaf4"
}Generated in
2025-01-20 20:49:53.700 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2025-01-20 20:49:53.700 | 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, 2804.75it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2729.34it/s]
2025-01-20 20:49:53.812 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s
free=29878800396288
Downloading weights
2025-01-20T20:49:53Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpfdhiihyh/weights url=https://replicate.delivery/xezq/ib77EhCvApL5CRmZgaPS8iZR3DuT2UZgJxDRpPSrb8ZufiDKA/trained_model.tar
2025-01-20T20:49:55Z | INFO | [ Complete ] dest=/tmp/tmpfdhiihyh/weights size="172 MB" total_elapsed=1.797s url=https://replicate.delivery/xezq/ib77EhCvApL5CRmZgaPS8iZR3DuT2UZgJxDRpPSrb8ZufiDKA/trained_model.tar
Downloaded weights in 1.82s
2025-01-20 20:49:55.636 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/f5a1b7cbc556f6f1
2025-01-20 20:49:55.706 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded
2025-01-20 20:49:55.706 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2025-01-20 20:49:55.707 | 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, 2809.63it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2734.23it/s]
2025-01-20 20:49:55.818 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.18s
Using seed: 50611
0it [00:00, ?it/s]
1it [00:00, 8.43it/s]
2it [00:00, 5.91it/s]
3it [00:00, 5.39it/s]
4it [00:00, 5.18it/s]
5it [00:00, 5.06it/s]
6it [00:01, 4.99it/s]
7it [00:01, 4.95it/s]
8it [00:01, 4.93it/s]
9it [00:01, 4.91it/s]
10it [00:01, 4.90it/s]
11it [00:02, 4.89it/s]
12it [00:02, 4.87it/s]
13it [00:02, 4.87it/s]
14it [00:02, 4.87it/s]
15it [00:02, 4.87it/s]
16it [00:03, 4.87it/s]
17it [00:03, 4.87it/s]
18it [00:03, 4.86it/s]
19it [00:03, 4.86it/s]
20it [00:04, 4.86it/s]
21it [00:04, 4.86it/s]
22it [00:04, 4.86it/s]
23it [00:04, 4.86it/s]
24it [00:04, 4.86it/s]
25it [00:05, 4.87it/s]
26it [00:05, 4.86it/s]
27it [00:05, 4.86it/s]
28it [00:05, 4.86it/s]
28it [00:05, 4.94it/s]
Total safe images: 1 out of 1