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sylvesteraswin /sylvester-flux-selfie:866dec74
Input
Run this model in Node.js with one line of code:
npm install replicate
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
import Replicate from "replicate";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});
Run sylvesteraswin/sylvester-flux-selfie using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"sylvesteraswin/sylvester-flux-selfie:866dec749879d1240d4bbef72b6efea5b968d845c7556bf7ba39a85dc010899c",
{
input: {
model: "dev",
height: 1440,
prompt: "A serene portrait of SYL_07_08, a 38-year-old Indian adult male with glasses and a man bun, standing in a golden field during sunset. A large, translucent bubble surrounds his face, catching the warm sunlight and creating soft, prismatic reflections. SYL_07_08 wears a simple black T-shirt, blending effortlessly into the dreamy, ethereal atmosphere. The warm hues of the setting sun bathe the scene in golden light, enhancing the natural beauty of the field and the gentle, surreal quality of the floating bubbles. The composition evokes a sense of tranquility and wonder. Photorealistic, UHD –ar 9:16 –style raw –v 6.0 –stylize 500.",
go_fast: false,
lora_scale: 1,
megapixels: "1",
num_outputs: 1,
aspect_ratio: "9:16",
output_format: "jpg",
guidance_scale: 3,
output_quality: 100,
prompt_strength: 0.5,
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.
pip install replicate
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
import replicate
Run sylvesteraswin/sylvester-flux-selfie using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"sylvesteraswin/sylvester-flux-selfie:866dec749879d1240d4bbef72b6efea5b968d845c7556bf7ba39a85dc010899c",
input={
"model": "dev",
"height": 1440,
"prompt": "A serene portrait of SYL_07_08, a 38-year-old Indian adult male with glasses and a man bun, standing in a golden field during sunset. A large, translucent bubble surrounds his face, catching the warm sunlight and creating soft, prismatic reflections. SYL_07_08 wears a simple black T-shirt, blending effortlessly into the dreamy, ethereal atmosphere. The warm hues of the setting sun bathe the scene in golden light, enhancing the natural beauty of the field and the gentle, surreal quality of the floating bubbles. The composition evokes a sense of tranquility and wonder. Photorealistic, UHD –ar 9:16 –style raw –v 6.0 –stylize 500.",
"go_fast": False,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 1,
"aspect_ratio": "9:16",
"output_format": "jpg",
"guidance_scale": 3,
"output_quality": 100,
"prompt_strength": 0.5,
"extra_lora_scale": 1,
"num_inference_steps": 28
}
)
print(output)
To learn more, take a look at the guide on getting started with Python.
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run sylvesteraswin/sylvester-flux-selfie 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": "sylvesteraswin/sylvester-flux-selfie:866dec749879d1240d4bbef72b6efea5b968d845c7556bf7ba39a85dc010899c",
"input": {
"model": "dev",
"height": 1440,
"prompt": "A serene portrait of SYL_07_08, a 38-year-old Indian adult male with glasses and a man bun, standing in a golden field during sunset. A large, translucent bubble surrounds his face, catching the warm sunlight and creating soft, prismatic reflections. SYL_07_08 wears a simple black T-shirt, blending effortlessly into the dreamy, ethereal atmosphere. The warm hues of the setting sun bathe the scene in golden light, enhancing the natural beauty of the field and the gentle, surreal quality of the floating bubbles. The composition evokes a sense of tranquility and wonder. Photorealistic, UHD –ar 9:16 –style raw –v 6.0 –stylize 500.",
"go_fast": false,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 1,
"aspect_ratio": "9:16",
"output_format": "jpg",
"guidance_scale": 3,
"output_quality": 100,
"prompt_strength": 0.5,
"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.
Add a payment method to run this model.
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Output
{
"completed_at": "2024-12-25T16:52:06.228586Z",
"created_at": "2024-12-25T16:51:54.315000Z",
"data_removed": false,
"error": null,
"id": "6y0nsk359drme0ckztxtyd7ck4",
"input": {
"model": "dev",
"height": 1440,
"prompt": "A serene portrait of SYL_07_08, a 38-year-old Indian adult male with glasses and a man bun, standing in a golden field during sunset. A large, translucent bubble surrounds his face, catching the warm sunlight and creating soft, prismatic reflections. SYL_07_08 wears a simple black T-shirt, blending effortlessly into the dreamy, ethereal atmosphere. The warm hues of the setting sun bathe the scene in golden light, enhancing the natural beauty of the field and the gentle, surreal quality of the floating bubbles. The composition evokes a sense of tranquility and wonder. Photorealistic, UHD –ar 9:16 –style raw –v 6.0 –stylize 500.",
"go_fast": false,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 1,
"aspect_ratio": "9:16",
"output_format": "jpg",
"guidance_scale": 3,
"output_quality": 100,
"prompt_strength": 0.5,
"extra_lora_scale": 1,
"num_inference_steps": 28
},
"logs": "2024-12-25 16:51:59.887 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2024-12-25 16:51:59.888 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 91%|█████████▏| 278/304 [00:00<00:00, 2766.71it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2577.31it/s]\n2024-12-25 16:52:00.006 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.12s\n2024-12-25 16:52:00.007 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/27c180b5b177085a\n2024-12-25 16:52:00.119 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2024-12-25 16:52:00.119 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2024-12-25 16:52:00.119 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 91%|█████████▏| 278/304 [00:00<00:00, 2768.73it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2579.03it/s]\n2024-12-25 16:52:00.238 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.23s\nUsing seed: 6146\n0it [00:00, ?it/s]\n1it [00:00, 8.46it/s]\n2it [00:00, 5.91it/s]\n3it [00:00, 5.38it/s]\n4it [00:00, 5.17it/s]\n5it [00:00, 5.05it/s]\n6it [00:01, 4.96it/s]\n7it [00:01, 4.92it/s]\n8it [00:01, 4.90it/s]\n9it [00:01, 4.89it/s]\n10it [00:01, 4.89it/s]\n11it [00:02, 4.87it/s]\n12it [00:02, 4.86it/s]\n13it [00:02, 4.86it/s]\n14it [00:02, 4.86it/s]\n15it [00:03, 4.85it/s]\n16it [00:03, 4.84it/s]\n17it [00:03, 4.84it/s]\n18it [00:03, 4.84it/s]\n19it [00:03, 4.84it/s]\n20it [00:04, 4.84it/s]\n21it [00:04, 4.84it/s]\n22it [00:04, 4.85it/s]\n23it [00:04, 4.85it/s]\n24it [00:04, 4.86it/s]\n25it [00:05, 4.85it/s]\n26it [00:05, 4.84it/s]\n27it [00:05, 4.84it/s]\n28it [00:05, 4.84it/s]\n28it [00:05, 4.92it/s]\nTotal safe images: 1 out of 1",
"metrics": {
"predict_time": 6.339903232,
"total_time": 11.913586
},
"output": [
"https://replicate.delivery/xezq/j3l7a7BHVZ64KVncu7P5tlSeZXWOVMPWMRfj1Y3yttr2oe8nA/out-0.jpg"
],
"started_at": "2024-12-25T16:51:59.888682Z",
"status": "succeeded",
"urls": {
"stream": "https://stream.replicate.com/v1/files/bcwr-cy73o7k3bgxvbkqyab744pzaqv4uqdn5novojthfivzqz6nkqnda",
"get": "https://api.replicate.com/v1/predictions/6y0nsk359drme0ckztxtyd7ck4",
"cancel": "https://api.replicate.com/v1/predictions/6y0nsk359drme0ckztxtyd7ck4/cancel"
},
"version": "866dec749879d1240d4bbef72b6efea5b968d845c7556bf7ba39a85dc010899c"
}
2024-12-25 16:51:59.887 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2024-12-25 16:51:59.888 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s]
Applying LoRA: 91%|█████████▏| 278/304 [00:00<00:00, 2766.71it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2577.31it/s]
2024-12-25 16:52:00.006 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.12s
2024-12-25 16:52:00.007 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/27c180b5b177085a
2024-12-25 16:52:00.119 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded
2024-12-25 16:52:00.119 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2024-12-25 16:52:00.119 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s]
Applying LoRA: 91%|█████████▏| 278/304 [00:00<00:00, 2768.73it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2579.03it/s]
2024-12-25 16:52:00.238 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.23s
Using seed: 6146
0it [00:00, ?it/s]
1it [00:00, 8.46it/s]
2it [00:00, 5.91it/s]
3it [00:00, 5.38it/s]
4it [00:00, 5.17it/s]
5it [00:00, 5.05it/s]
6it [00:01, 4.96it/s]
7it [00:01, 4.92it/s]
8it [00:01, 4.90it/s]
9it [00:01, 4.89it/s]
10it [00:01, 4.89it/s]
11it [00:02, 4.87it/s]
12it [00:02, 4.86it/s]
13it [00:02, 4.86it/s]
14it [00:02, 4.86it/s]
15it [00:03, 4.85it/s]
16it [00:03, 4.84it/s]
17it [00:03, 4.84it/s]
18it [00:03, 4.84it/s]
19it [00:03, 4.84it/s]
20it [00:04, 4.84it/s]
21it [00:04, 4.84it/s]
22it [00:04, 4.85it/s]
23it [00:04, 4.85it/s]
24it [00:04, 4.86it/s]
25it [00:05, 4.85it/s]
26it [00:05, 4.84it/s]
27it [00:05, 4.84it/s]
28it [00:05, 4.84it/s]
28it [00:05, 4.92it/s]
Total safe images: 1 out of 1