Prediction

f19j1xcbjhrm60chfggrsgcqzc

Status

Succeeded

Source

Web

Hardware

H100

Total duration

38.9s

Created

10 months ago

Input

model: dev
prompt: a portrait of 0_1 woman standing as a distant hiker in a moody landscape, perfect eyes
lora_scale: 0.9
num_outputs: 4
aspect_ratio: 16:9
output_format: webp
guidance_scale: 2.5
output_quality: 90
num_inference_steps: 28

{
  "model": "dev",
  "prompt": "a portrait of 0_1 woman standing as a distant hiker in a moody landscape, perfect eyes",
  "lora_scale": 0.9,
  "num_outputs": 4,
  "aspect_ratio": "16:9",
  "output_format": "webp",
  "guidance_scale": 2.5,
  "output_quality": 90,
  "num_inference_steps": 28
}

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 fofr/0_1-webp using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "fofr/0_1-webp:e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7",
  {
    input: {
      model: "dev",
      prompt: "a portrait of 0_1 woman standing as a distant hiker in a moody landscape, perfect eyes",
      lora_scale: 0.9,
      num_outputs: 4,
      aspect_ratio: "16:9",
      output_format: "webp",
      guidance_scale: 2.5,
      output_quality: 90,
      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

Import the client:

import replicate

Run fofr/0_1-webp using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "fofr/0_1-webp:e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7",
    input={
        "model": "dev",
        "prompt": "a portrait of 0_1 woman standing as a distant hiker in a moody landscape, perfect eyes",
        "lora_scale": 0.9,
        "num_outputs": 4,
        "aspect_ratio": "16:9",
        "output_format": "webp",
        "guidance_scale": 2.5,
        "output_quality": 90,
        "num_inference_steps": 28
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Run fofr/0_1-webp 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": "fofr/0_1-webp:e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7",
    "input": {
      "model": "dev",
      "prompt": "a portrait of 0_1 woman standing as a distant hiker in a moody landscape, perfect eyes",
      "lora_scale": 0.9,
      "num_outputs": 4,
      "aspect_ratio": "16:9",
      "output_format": "webp",
      "guidance_scale": 2.5,
      "output_quality": 90,
      "num_inference_steps": 28
    }
  }' \
  https://api.replicate.com/v1/predictions

To 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 cog

If 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/fofr/0_1-webp@sha256:e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7 \
  -i 'model="dev"' \
  -i 'prompt="a portrait of 0_1 woman standing as a distant hiker in a moody landscape, perfect eyes"' \
  -i 'lora_scale=0.9' \
  -i 'num_outputs=4' \
  -i 'aspect_ratio="16:9"' \
  -i 'output_format="webp"' \
  -i 'guidance_scale=2.5' \
  -i 'output_quality=90' \
  -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/fofr/0_1-webp@sha256:e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "model": "dev",
      "prompt": "a portrait of 0_1 woman standing as a distant hiker in a moody landscape, perfect eyes",
      "lora_scale": 0.9,
      "num_outputs": 4,
      "aspect_ratio": "16:9",
      "output_format": "webp",
      "guidance_scale": 2.5,
      "output_quality": 90,
      "num_inference_steps": 28
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

{
  "completed_at": "2024-08-22T22:08:17.764346Z",
  "created_at": "2024-08-22T22:07:38.900000Z",
  "data_removed": false,
  "error": null,
  "id": "f19j1xcbjhrm60chfggrsgcqzc",
  "input": {
    "model": "dev",
    "prompt": "a portrait of 0_1 woman standing as a distant hiker in a moody landscape, perfect eyes",
    "lora_scale": 0.9,
    "num_outputs": 4,
    "aspect_ratio": "16:9",
    "output_format": "webp",
    "guidance_scale": 2.5,
    "output_quality": 90,
    "num_inference_steps": 28
  },
  "logs": "Using seed: 51482\nPrompt: a portrait of 0_1 woman standing as a distant hiker in a moody landscape, perfect eyes\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nLoRA weights loaded successfully\n  0%|          | 0/28 [00:00<?, ?it/s]\n  4%|▎         | 1/28 [00:01<00:27,  1.00s/it]\n  7%|▋         | 2/28 [00:01<00:22,  1.13it/s]\n 11%|█         | 3/28 [00:02<00:23,  1.07it/s]\n 14%|█▍        | 4/28 [00:03<00:23,  1.04it/s]\n 18%|█▊        | 5/28 [00:04<00:22,  1.02it/s]\n 21%|██▏       | 6/28 [00:05<00:21,  1.02it/s]\n 25%|██▌       | 7/28 [00:06<00:20,  1.01it/s]\n 29%|██▊       | 8/28 [00:07<00:19,  1.01it/s]\n 32%|███▏      | 9/28 [00:08<00:18,  1.00it/s]\n 36%|███▌      | 10/28 [00:09<00:17,  1.00it/s]\n 39%|███▉      | 11/28 [00:10<00:16,  1.00it/s]\n 43%|████▎     | 12/28 [00:11<00:15,  1.00it/s]\n 46%|████▋     | 13/28 [00:12<00:15,  1.00s/it]\n 50%|█████     | 14/28 [00:13<00:14,  1.00s/it]\n 54%|█████▎    | 15/28 [00:14<00:13,  1.00s/it]\n 57%|█████▋    | 16/28 [00:15<00:12,  1.00s/it]\n 61%|██████    | 17/28 [00:16<00:11,  1.00s/it]\n 64%|██████▍   | 18/28 [00:17<00:10,  1.00s/it]\n 68%|██████▊   | 19/28 [00:18<00:09,  1.00s/it]\n 71%|███████▏  | 20/28 [00:19<00:08,  1.00s/it]\n 75%|███████▌  | 21/28 [00:20<00:07,  1.00s/it]\n 79%|███████▊  | 22/28 [00:21<00:06,  1.00s/it]\n 82%|████████▏ | 23/28 [00:22<00:05,  1.00s/it]\n 86%|████████▌ | 24/28 [00:23<00:04,  1.00s/it]\n 89%|████████▉ | 25/28 [00:24<00:03,  1.00s/it]\n 93%|█████████▎| 26/28 [00:25<00:02,  1.00s/it]\n 96%|█████████▋| 27/28 [00:26<00:01,  1.00s/it]\n100%|██████████| 28/28 [00:27<00:00,  1.00s/it]\n100%|██████████| 28/28 [00:27<00:00,  1.01it/s]\nPotential NSFW content was detected in one or more images. A black image will be returned instead. Try again with a different prompt and/or seed.\nNSFW content detected in image 1\nNSFW content detected in image 2",
  "metrics": {
    "predict_time": 38.142841806,
    "total_time": 38.864346
  },
  "output": [
    "https://replicate.delivery/yhqm/wRLqneE7A2RYbSNPuTDfTzK5UDKpoe7IH0fv6f5iJyffoRrqJA/out-0.webp",
    "https://replicate.delivery/yhqm/xuFXNmclez0RFSazRfLhS3UgEntTMqYN8fjaE1MzWZJjGtqmA/out-3.webp"
  ],
  "started_at": "2024-08-22T22:07:39.621504Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/f19j1xcbjhrm60chfggrsgcqzc",
    "cancel": "https://api.replicate.com/v1/predictions/f19j1xcbjhrm60chfggrsgcqzc/cancel"
  },
  "version": "e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7"
}

Generated in

38.1 seconds

fofr/0_1-webp:e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7

Using seed: 51482
Prompt: a portrait of 0_1 woman standing as a distant hiker in a moody landscape, perfect eyes
txt2img mode
Using dev model
Loading LoRA weights
LoRA weights loaded successfully
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Potential NSFW content was detected in one or more images. A black image will be returned instead. Try again with a different prompt and/or seed.
NSFW content detected in image 1
NSFW content detected in image 2

Prediction

Model

p28166hdgnrm20chdygssqtbt8

Status

Succeeded

Source

Web

Hardware

H100

Total duration

32m 6s

Created

10 months ago

Input

model: dev
prompt: a portrait photo of 0_1, a cyberpunk woman on a street in the rain
lora_scale: 1
num_outputs: 4
aspect_ratio: 1:1
output_format: webp
guidance_scale: 2.5
output_quality: 80
num_inference_steps: 28

{
  "model": "dev",
  "prompt": "a portrait photo of 0_1, a cyberpunk woman on a street in the rain",
  "lora_scale": 1,
  "num_outputs": 4,
  "aspect_ratio": "1:1",
  "output_format": "webp",
  "guidance_scale": 2.5,
  "output_quality": 80,
  "num_inference_steps": 28
}

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 fofr/0_1-webp using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "fofr/0_1-webp:e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7",
  {
    input: {
      model: "dev",
      prompt: "a portrait photo of 0_1, a cyberpunk woman on a street in the rain",
      lora_scale: 1,
      num_outputs: 4,
      aspect_ratio: "1:1",
      output_format: "webp",
      guidance_scale: 2.5,
      output_quality: 80,
      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

Import the client:

import replicate

Run fofr/0_1-webp using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "fofr/0_1-webp:e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7",
    input={
        "model": "dev",
        "prompt": "a portrait photo of 0_1, a cyberpunk woman on a street in the rain",
        "lora_scale": 1,
        "num_outputs": 4,
        "aspect_ratio": "1:1",
        "output_format": "webp",
        "guidance_scale": 2.5,
        "output_quality": 80,
        "num_inference_steps": 28
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Run fofr/0_1-webp 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": "fofr/0_1-webp:e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7",
    "input": {
      "model": "dev",
      "prompt": "a portrait photo of 0_1, a cyberpunk woman on a street in the rain",
      "lora_scale": 1,
      "num_outputs": 4,
      "aspect_ratio": "1:1",
      "output_format": "webp",
      "guidance_scale": 2.5,
      "output_quality": 80,
      "num_inference_steps": 28
    }
  }' \
  https://api.replicate.com/v1/predictions

To 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 cog

If 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/fofr/0_1-webp@sha256:e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7 \
  -i 'model="dev"' \
  -i 'prompt="a portrait photo of 0_1, a cyberpunk woman on a street in the rain"' \
  -i 'lora_scale=1' \
  -i 'num_outputs=4' \
  -i 'aspect_ratio="1:1"' \
  -i 'output_format="webp"' \
  -i 'guidance_scale=2.5' \
  -i 'output_quality=80' \
  -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/fofr/0_1-webp@sha256:e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "model": "dev",
      "prompt": "a portrait photo of 0_1, a cyberpunk woman on a street in the rain",
      "lora_scale": 1,
      "num_outputs": 4,
      "aspect_ratio": "1:1",
      "output_format": "webp",
      "guidance_scale": 2.5,
      "output_quality": 80,
      "num_inference_steps": 28
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

{
  "completed_at": "2024-08-20T12:24:05.976537Z",
  "created_at": "2024-08-20T11:51:59.621000Z",
  "data_removed": false,
  "error": null,
  "id": "p28166hdgnrm20chdygssqtbt8",
  "input": {
    "model": "dev",
    "prompt": "a portrait photo of 0_1, a cyberpunk woman on a street in the rain",
    "lora_scale": 1,
    "num_outputs": 4,
    "aspect_ratio": "1:1",
    "output_format": "webp",
    "guidance_scale": 2.5,
    "output_quality": 80,
    "num_inference_steps": 28
  },
  "logs": "Using seed: 32357\nPrompt: a portrait photo of 0_1, a cyberpunk woman on a street in the rain\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nLoRA weights loaded successfully\n  0%|          | 0/28 [00:00<?, ?it/s]\n  4%|▎         | 1/28 [00:01<00:27,  1.01s/it]\n  7%|▋         | 2/28 [00:01<00:22,  1.14it/s]\n 11%|█         | 3/28 [00:02<00:23,  1.06it/s]\n 14%|█▍        | 4/28 [00:03<00:23,  1.03it/s]\n 18%|█▊        | 5/28 [00:04<00:22,  1.02it/s]\n 21%|██▏       | 6/28 [00:05<00:21,  1.01it/s]\n 25%|██▌       | 7/28 [00:06<00:21,  1.00s/it]\n 29%|██▊       | 8/28 [00:07<00:20,  1.00s/it]\n 32%|███▏      | 9/28 [00:08<00:19,  1.01s/it]\n 36%|███▌      | 10/28 [00:09<00:18,  1.01s/it]\n 39%|███▉      | 11/28 [00:10<00:17,  1.01s/it]\n 43%|████▎     | 12/28 [00:11<00:16,  1.01s/it]\n 46%|████▋     | 13/28 [00:12<00:15,  1.01s/it]\n 50%|█████     | 14/28 [00:13<00:14,  1.01s/it]\n 54%|█████▎    | 15/28 [00:14<00:13,  1.01s/it]\n 57%|█████▋    | 16/28 [00:15<00:12,  1.01s/it]\n 61%|██████    | 17/28 [00:17<00:11,  1.01s/it]\n 64%|██████▍   | 18/28 [00:18<00:10,  1.02s/it]\n 68%|██████▊   | 19/28 [00:19<00:09,  1.02s/it]\n 71%|███████▏  | 20/28 [00:20<00:08,  1.02s/it]\n 75%|███████▌  | 21/28 [00:21<00:07,  1.02s/it]\n 79%|███████▊  | 22/28 [00:22<00:06,  1.02s/it]\n 82%|████████▏ | 23/28 [00:23<00:05,  1.02s/it]\n 86%|████████▌ | 24/28 [00:24<00:04,  1.02s/it]\n 89%|████████▉ | 25/28 [00:25<00:03,  1.02s/it]\n 93%|█████████▎| 26/28 [00:26<00:02,  1.02s/it]\n 96%|█████████▋| 27/28 [00:27<00:01,  1.02s/it]\n100%|██████████| 28/28 [00:28<00:00,  1.02s/it]\n100%|██████████| 28/28 [00:28<00:00,  1.01s/it]",
  "metrics": {
    "predict_time": 111.649415539,
    "total_time": 1926.355537
  },
  "output": [
    "https://replicate.delivery/yhqm/V5TjzSyVkbaNLh1CgsCiLMCKFOrEXFc8wcfOxku6MH1y5RqJA/out-0.webp",
    "https://replicate.delivery/yhqm/vRsifltg9ei7fJ74z3ng85FP5AjSSlk2vBEfetQsLd9rceI1E/out-1.webp",
    "https://replicate.delivery/yhqm/sT4jSLLzB95DOdVU8IL3KQ3xz9LQJBTb6XbK8XjLBlfy5RqJA/out-2.webp",
    "https://replicate.delivery/yhqm/rIcU61qfGMTnVyJ0DTQW1WgiVPTuiBSCfdBaX6N2Ph1lzjUTA/out-3.webp"
  ],
  "started_at": "2024-08-20T12:22:14.327121Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/p28166hdgnrm20chdygssqtbt8",
    "cancel": "https://api.replicate.com/v1/predictions/p28166hdgnrm20chdygssqtbt8/cancel"
  },
  "version": "e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7"
}

Generated in

1 minute 52 seconds

fofr/0_1-webp:e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7

Prediction

Model

sthe3aedg9rm00che0xbk475xw

Status

Succeeded

Source

Web

Hardware

H100

Total duration

20.4s

Created

10 months ago

Input

model: dev
prompt: a portrait photo of 0_1 as a charismatic female speaker at conference, captured gesturing mid-speech on stage. She is wearing a light grey sweater. She's also wearing a simple black lanyard hanging around her neck. The lanyard badge has the text "Replicate". She has perfect eyes. Behind her, there is a blurred background with a white banner containing logos and text (including replicate), a professional conference setting.
lora_scale: 0.9
num_outputs: 1
aspect_ratio: 3:4
output_format: webp
guidance_scale: 2.5
output_quality: 90
num_inference_steps: 28

{
  "model": "dev",
  "prompt": "a portrait photo of 0_1 as a charismatic female speaker at conference, captured gesturing mid-speech on stage. She is wearing a light grey sweater. She's also wearing a simple black lanyard hanging around her neck. The lanyard badge has the text \"Replicate\". She has perfect eyes.\n\nBehind her, there is a blurred background with a white banner containing logos and text (including replicate), a professional conference setting.",
  "lora_scale": 0.9,
  "num_outputs": 1,
  "aspect_ratio": "3:4",
  "output_format": "webp",
  "guidance_scale": 2.5,
  "output_quality": 90,
  "num_inference_steps": 28
}

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 fofr/0_1-webp using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "fofr/0_1-webp:e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7",
  {
    input: {
      model: "dev",
      prompt: "a portrait photo of 0_1 as a charismatic female speaker at conference, captured gesturing mid-speech on stage. She is wearing a light grey sweater. She's also wearing a simple black lanyard hanging around her neck. The lanyard badge has the text \"Replicate\". She has perfect eyes.\n\nBehind her, there is a blurred background with a white banner containing logos and text (including replicate), a professional conference setting.",
      lora_scale: 0.9,
      num_outputs: 1,
      aspect_ratio: "3:4",
      output_format: "webp",
      guidance_scale: 2.5,
      output_quality: 90,
      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

Import the client:

import replicate

Run fofr/0_1-webp using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "fofr/0_1-webp:e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7",
    input={
        "model": "dev",
        "prompt": "a portrait photo of 0_1 as a charismatic female speaker at conference, captured gesturing mid-speech on stage. She is wearing a light grey sweater. She's also wearing a simple black lanyard hanging around her neck. The lanyard badge has the text \"Replicate\". She has perfect eyes.\n\nBehind her, there is a blurred background with a white banner containing logos and text (including replicate), a professional conference setting.",
        "lora_scale": 0.9,
        "num_outputs": 1,
        "aspect_ratio": "3:4",
        "output_format": "webp",
        "guidance_scale": 2.5,
        "output_quality": 90,
        "num_inference_steps": 28
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Run fofr/0_1-webp 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": "fofr/0_1-webp:e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7",
    "input": {
      "model": "dev",
      "prompt": "a portrait photo of 0_1 as a charismatic female speaker at conference, captured gesturing mid-speech on stage. She is wearing a light grey sweater. She\'s also wearing a simple black lanyard hanging around her neck. The lanyard badge has the text \\"Replicate\\". She has perfect eyes.\\n\\nBehind her, there is a blurred background with a white banner containing logos and text (including replicate), a professional conference setting.",
      "lora_scale": 0.9,
      "num_outputs": 1,
      "aspect_ratio": "3:4",
      "output_format": "webp",
      "guidance_scale": 2.5,
      "output_quality": 90,
      "num_inference_steps": 28
    }
  }' \
  https://api.replicate.com/v1/predictions

To 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 cog

If 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/fofr/0_1-webp@sha256:e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7 \
  -i 'model="dev"' \
  -i $'prompt="a portrait photo of 0_1 as a charismatic female speaker at conference, captured gesturing mid-speech on stage. She is wearing a light grey sweater. She\'s also wearing a simple black lanyard hanging around her neck. The lanyard badge has the text \\"Replicate\\". She has perfect eyes.\\n\\nBehind her, there is a blurred background with a white banner containing logos and text (including replicate), a professional conference setting."' \
  -i 'lora_scale=0.9' \
  -i 'num_outputs=1' \
  -i 'aspect_ratio="3:4"' \
  -i 'output_format="webp"' \
  -i 'guidance_scale=2.5' \
  -i 'output_quality=90' \
  -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/fofr/0_1-webp@sha256:e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "model": "dev",
      "prompt": "a portrait photo of 0_1 as a charismatic female speaker at conference, captured gesturing mid-speech on stage. She is wearing a light grey sweater. She\'s also wearing a simple black lanyard hanging around her neck. The lanyard badge has the text \\"Replicate\\". She has perfect eyes.\\n\\nBehind her, there is a blurred background with a white banner containing logos and text (including replicate), a professional conference setting.",
      "lora_scale": 0.9,
      "num_outputs": 1,
      "aspect_ratio": "3:4",
      "output_format": "webp",
      "guidance_scale": 2.5,
      "output_quality": 90,
      "num_inference_steps": 28
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

{
  "completed_at": "2024-08-20T14:40:07.946202Z",
  "created_at": "2024-08-20T14:39:47.586000Z",
  "data_removed": false,
  "error": null,
  "id": "sthe3aedg9rm00che0xbk475xw",
  "input": {
    "model": "dev",
    "prompt": "a portrait photo of 0_1 as a charismatic female speaker at conference, captured gesturing mid-speech on stage. She is wearing a light grey sweater. She's also wearing a simple black lanyard hanging around her neck. The lanyard badge has the text \"Replicate\". She has perfect eyes.\n\nBehind her, there is a blurred background with a white banner containing logos and text (including replicate), a professional conference setting.",
    "lora_scale": 0.9,
    "num_outputs": 1,
    "aspect_ratio": "3:4",
    "output_format": "webp",
    "guidance_scale": 2.5,
    "output_quality": 90,
    "num_inference_steps": 28
  },
  "logs": "Using seed: 2697\nPrompt: a portrait photo of 0_1 as a charismatic female speaker at conference, captured gesturing mid-speech on stage. She is wearing a light grey sweater. She's also wearing a simple black lanyard hanging around her neck. The lanyard badge has the text \"Replicate\". She has perfect eyes.\nBehind her, there is a blurred background with a white banner containing logos and text (including replicate), a professional conference setting.\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nLoRA weights loaded successfully\nThe following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['text ( including replicate ), a professional conference setting.']\n  0%|          | 0/28 [00:00<?, ?it/s]\n  4%|▎         | 1/28 [00:00<00:07,  3.55it/s]\n  7%|▋         | 2/28 [00:00<00:06,  3.97it/s]\n 11%|█         | 3/28 [00:00<00:06,  3.77it/s]\n 14%|█▍        | 4/28 [00:01<00:06,  3.68it/s]\n 18%|█▊        | 5/28 [00:01<00:06,  3.64it/s]\n 21%|██▏       | 6/28 [00:01<00:06,  3.61it/s]\n 25%|██▌       | 7/28 [00:01<00:05,  3.59it/s]\n 29%|██▊       | 8/28 [00:02<00:05,  3.58it/s]\n 32%|███▏      | 9/28 [00:02<00:05,  3.58it/s]\n 36%|███▌      | 10/28 [00:02<00:05,  3.57it/s]\n 39%|███▉      | 11/28 [00:03<00:04,  3.57it/s]\n 43%|████▎     | 12/28 [00:03<00:04,  3.56it/s]\n 46%|████▋     | 13/28 [00:03<00:04,  3.57it/s]\n 50%|█████     | 14/28 [00:03<00:03,  3.56it/s]\n 54%|█████▎    | 15/28 [00:04<00:03,  3.56it/s]\n 57%|█████▋    | 16/28 [00:04<00:03,  3.56it/s]\n 61%|██████    | 17/28 [00:04<00:03,  3.56it/s]\n 64%|██████▍   | 18/28 [00:05<00:02,  3.55it/s]\n 68%|██████▊   | 19/28 [00:05<00:02,  3.55it/s]\n 71%|███████▏  | 20/28 [00:05<00:02,  3.56it/s]\n 75%|███████▌  | 21/28 [00:05<00:01,  3.56it/s]\n 79%|███████▊  | 22/28 [00:06<00:01,  3.56it/s]\n 82%|████████▏ | 23/28 [00:06<00:01,  3.56it/s]\n 86%|████████▌ | 24/28 [00:06<00:01,  3.56it/s]\n 89%|████████▉ | 25/28 [00:06<00:00,  3.56it/s]\n 93%|█████████▎| 26/28 [00:07<00:00,  3.56it/s]\n 96%|█████████▋| 27/28 [00:07<00:00,  3.56it/s]\n100%|██████████| 28/28 [00:07<00:00,  3.56it/s]\n100%|██████████| 28/28 [00:07<00:00,  3.58it/s]",
  "metrics": {
    "predict_time": 16.173941447,
    "total_time": 20.360202
  },
  "output": [
    "https://replicate.delivery/yhqm/zNGay29l8SqjGBbhaPhXxfW3txrcpUbFcEgGPws6eBXHzlUTA/out-0.webp"
  ],
  "started_at": "2024-08-20T14:39:51.772260Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/sthe3aedg9rm00che0xbk475xw",
    "cancel": "https://api.replicate.com/v1/predictions/sthe3aedg9rm00che0xbk475xw/cancel"
  },
  "version": "e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7"
}

Generated in

16.2 seconds

fofr/0_1-webp:e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7

Using seed: 2697
Prompt: a portrait photo of 0_1 as a charismatic female speaker at conference, captured gesturing mid-speech on stage. She is wearing a light grey sweater. She's also wearing a simple black lanyard hanging around her neck. The lanyard badge has the text "Replicate". She has perfect eyes.
Behind her, there is a blurred background with a white banner containing logos and text (including replicate), a professional conference setting.
txt2img mode
Using dev model
Loading LoRA weights
LoRA weights loaded successfully
The following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['text ( including replicate ), a professional conference setting.']
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Prediction

Model

jt4kzbg0bnrm60che14asvhcdc

Status

Succeeded

Source

Web

Hardware

H100

Total duration

50.8s

Created

10 months ago

Input

model: dev
prompt: A portrait photo of 0_1 as a charismatic female chef in a bustling kitchen, captured mid-action while cooking. She is wearing a crisp white chef's coat. She's also wearing a simple blue apron with the restaurant's logo embroidered on it. The apron strings are neatly tied around her waist. She has perfect eyes. Behind her, there is a blurred background of a professional kitchen setting. Stainless steel appliances and cookware are visible, along with other chefs working in the background. On the wall, there's a chalkboard menu with the day's specials written in elegant handwriting.
lora_scale: 0.9
num_outputs: 4
aspect_ratio: 3:4
output_format: webp
guidance_scale: 2.5
output_quality: 90
num_inference_steps: 28

{
  "model": "dev",
  "prompt": "A portrait photo of 0_1 as a charismatic female chef in a bustling kitchen, captured mid-action while cooking. She is wearing a crisp white chef's coat. She's also wearing a simple blue apron with the restaurant's logo embroidered on it. The apron strings are neatly tied around her waist. She has perfect eyes.\nBehind her, there is a blurred background of a professional kitchen setting. Stainless steel appliances and cookware are visible, along with other chefs working in the background. On the wall, there's a chalkboard menu with the day's specials written in elegant handwriting.",
  "lora_scale": 0.9,
  "num_outputs": 4,
  "aspect_ratio": "3:4",
  "output_format": "webp",
  "guidance_scale": 2.5,
  "output_quality": 90,
  "num_inference_steps": 28
}

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 fofr/0_1-webp using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "fofr/0_1-webp:e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7",
  {
    input: {
      model: "dev",
      prompt: "A portrait photo of 0_1 as a charismatic female chef in a bustling kitchen, captured mid-action while cooking. She is wearing a crisp white chef's coat. She's also wearing a simple blue apron with the restaurant's logo embroidered on it. The apron strings are neatly tied around her waist. She has perfect eyes.\nBehind her, there is a blurred background of a professional kitchen setting. Stainless steel appliances and cookware are visible, along with other chefs working in the background. On the wall, there's a chalkboard menu with the day's specials written in elegant handwriting.",
      lora_scale: 0.9,
      num_outputs: 4,
      aspect_ratio: "3:4",
      output_format: "webp",
      guidance_scale: 2.5,
      output_quality: 90,
      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

Import the client:

import replicate

Run fofr/0_1-webp using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "fofr/0_1-webp:e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7",
    input={
        "model": "dev",
        "prompt": "A portrait photo of 0_1 as a charismatic female chef in a bustling kitchen, captured mid-action while cooking. She is wearing a crisp white chef's coat. She's also wearing a simple blue apron with the restaurant's logo embroidered on it. The apron strings are neatly tied around her waist. She has perfect eyes.\nBehind her, there is a blurred background of a professional kitchen setting. Stainless steel appliances and cookware are visible, along with other chefs working in the background. On the wall, there's a chalkboard menu with the day's specials written in elegant handwriting.",
        "lora_scale": 0.9,
        "num_outputs": 4,
        "aspect_ratio": "3:4",
        "output_format": "webp",
        "guidance_scale": 2.5,
        "output_quality": 90,
        "num_inference_steps": 28
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Run fofr/0_1-webp 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": "fofr/0_1-webp:e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7",
    "input": {
      "model": "dev",
      "prompt": "A portrait photo of 0_1 as a charismatic female chef in a bustling kitchen, captured mid-action while cooking. She is wearing a crisp white chef\'s coat. She\'s also wearing a simple blue apron with the restaurant\'s logo embroidered on it. The apron strings are neatly tied around her waist. She has perfect eyes.\\nBehind her, there is a blurred background of a professional kitchen setting. Stainless steel appliances and cookware are visible, along with other chefs working in the background. On the wall, there\'s a chalkboard menu with the day\'s specials written in elegant handwriting.",
      "lora_scale": 0.9,
      "num_outputs": 4,
      "aspect_ratio": "3:4",
      "output_format": "webp",
      "guidance_scale": 2.5,
      "output_quality": 90,
      "num_inference_steps": 28
    }
  }' \
  https://api.replicate.com/v1/predictions

To 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 cog

If 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/fofr/0_1-webp@sha256:e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7 \
  -i 'model="dev"' \
  -i $'prompt="A portrait photo of 0_1 as a charismatic female chef in a bustling kitchen, captured mid-action while cooking. She is wearing a crisp white chef\'s coat. She\'s also wearing a simple blue apron with the restaurant\'s logo embroidered on it. The apron strings are neatly tied around her waist. She has perfect eyes.\\nBehind her, there is a blurred background of a professional kitchen setting. Stainless steel appliances and cookware are visible, along with other chefs working in the background. On the wall, there\'s a chalkboard menu with the day\'s specials written in elegant handwriting."' \
  -i 'lora_scale=0.9' \
  -i 'num_outputs=4' \
  -i 'aspect_ratio="3:4"' \
  -i 'output_format="webp"' \
  -i 'guidance_scale=2.5' \
  -i 'output_quality=90' \
  -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/fofr/0_1-webp@sha256:e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "model": "dev",
      "prompt": "A portrait photo of 0_1 as a charismatic female chef in a bustling kitchen, captured mid-action while cooking. She is wearing a crisp white chef\'s coat. She\'s also wearing a simple blue apron with the restaurant\'s logo embroidered on it. The apron strings are neatly tied around her waist. She has perfect eyes.\\nBehind her, there is a blurred background of a professional kitchen setting. Stainless steel appliances and cookware are visible, along with other chefs working in the background. On the wall, there\'s a chalkboard menu with the day\'s specials written in elegant handwriting.",
      "lora_scale": 0.9,
      "num_outputs": 4,
      "aspect_ratio": "3:4",
      "output_format": "webp",
      "guidance_scale": 2.5,
      "output_quality": 90,
      "num_inference_steps": 28
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

{
  "completed_at": "2024-08-20T14:55:03.331828Z",
  "created_at": "2024-08-20T14:54:12.573000Z",
  "data_removed": false,
  "error": null,
  "id": "jt4kzbg0bnrm60che14asvhcdc",
  "input": {
    "model": "dev",
    "prompt": "A portrait photo of 0_1 as a charismatic female chef in a bustling kitchen, captured mid-action while cooking. She is wearing a crisp white chef's coat. She's also wearing a simple blue apron with the restaurant's logo embroidered on it. The apron strings are neatly tied around her waist. She has perfect eyes.\nBehind her, there is a blurred background of a professional kitchen setting. Stainless steel appliances and cookware are visible, along with other chefs working in the background. On the wall, there's a chalkboard menu with the day's specials written in elegant handwriting.",
    "lora_scale": 0.9,
    "num_outputs": 4,
    "aspect_ratio": "3:4",
    "output_format": "webp",
    "guidance_scale": 2.5,
    "output_quality": 90,
    "num_inference_steps": 28
  },
  "logs": "Using seed: 35130\nPrompt: A portrait photo of 0_1 as a charismatic female chef in a bustling kitchen, captured mid-action while cooking. She is wearing a crisp white chef's coat. She's also wearing a simple blue apron with the restaurant's logo embroidered on it. The apron strings are neatly tied around her waist. She has perfect eyes.\nBehind her, there is a blurred background of a professional kitchen setting. Stainless steel appliances and cookware are visible, along with other chefs working in the background. On the wall, there's a chalkboard menu with the day's specials written in elegant handwriting.\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nEnsuring enough disk space...\nFree disk space: 9653500030976\nDownloading weights\n2024-08-20T14:54:24Z | INFO  | [ Initiating ] chunk_size=150M dest=/src/weights-cache/aa2152eb914fa84c url=https://replicate.delivery/yhqm/EgcoMuFe78SkBCR2lRD2Stf7KXN2tdWBJwwdl62xqNZEtWUTA/trained_model.tar\n2024-08-20T14:54:25Z | INFO  | [ Complete ] dest=/src/weights-cache/aa2152eb914fa84c size=\"172 MB\" total_elapsed=1.443s url=https://replicate.delivery/yhqm/EgcoMuFe78SkBCR2lRD2Stf7KXN2tdWBJwwdl62xqNZEtWUTA/trained_model.tar\nb''\nDownloaded weights in 1.466421127319336 seconds\nLoRA weights loaded successfully\nToken indices sequence length is longer than the specified maximum sequence length for this model (122 > 77). Running this sequence through the model will result in indexing errors\nThe following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: [\"background of a professional kitchen setting. stainless steel appliances and cookware are visible, along with other chefs working in the background. on the wall, there's a chalkboard menu with the day's specials written in elegant handwriting.\", \"background of a professional kitchen setting. stainless steel appliances and cookware are visible, along with other chefs working in the background. on the wall, there's a chalkboard menu with the day's specials written in elegant handwriting.\", \"background of a professional kitchen setting. stainless steel appliances and cookware are visible, along with other chefs working in the background. on the wall, there's a chalkboard menu with the day's specials written in elegant handwriting.\", \"background of a professional kitchen setting. stainless steel appliances and cookware are visible, along with other chefs working in the background. on the wall, there's a chalkboard menu with the day's specials written in elegant handwriting.\"]\n  0%|          | 0/28 [00:00<?, ?it/s]\n  4%|▎         | 1/28 [00:01<00:27,  1.00s/it]\n  7%|▋         | 2/28 [00:01<00:22,  1.13it/s]\n 11%|█         | 3/28 [00:02<00:23,  1.06it/s]\n 14%|█▍        | 4/28 [00:03<00:23,  1.03it/s]\n 18%|█▊        | 5/28 [00:04<00:22,  1.02it/s]\n 21%|██▏       | 6/28 [00:05<00:21,  1.01it/s]\n 25%|██▌       | 7/28 [00:06<00:20,  1.00it/s]\n 29%|██▊       | 8/28 [00:07<00:19,  1.00it/s]\n 32%|███▏      | 9/28 [00:08<00:19,  1.00s/it]\n 36%|███▌      | 10/28 [00:09<00:18,  1.00s/it]\n 39%|███▉      | 11/28 [00:10<00:17,  1.01s/it]\n 43%|████▎     | 12/28 [00:11<00:16,  1.01s/it]\n 46%|████▋     | 13/28 [00:12<00:15,  1.01s/it]\n 50%|█████     | 14/28 [00:13<00:14,  1.01s/it]\n 54%|█████▎    | 15/28 [00:14<00:13,  1.01s/it]\n 57%|█████▋    | 16/28 [00:15<00:12,  1.01s/it]\n 61%|██████    | 17/28 [00:16<00:11,  1.01s/it]\n 64%|██████▍   | 18/28 [00:17<00:10,  1.01s/it]\n 68%|██████▊   | 19/28 [00:18<00:09,  1.01s/it]\n 71%|███████▏  | 20/28 [00:19<00:08,  1.01s/it]\n 75%|███████▌  | 21/28 [00:20<00:07,  1.01s/it]\n 79%|███████▊  | 22/28 [00:21<00:06,  1.01s/it]\n 82%|████████▏ | 23/28 [00:22<00:05,  1.01s/it]\n 86%|████████▌ | 24/28 [00:23<00:04,  1.01s/it]\n 89%|████████▉ | 25/28 [00:24<00:03,  1.01s/it]\n 93%|█████████▎| 26/28 [00:25<00:02,  1.01s/it]\n 96%|█████████▋| 27/28 [00:26<00:01,  1.00s/it]\n100%|██████████| 28/28 [00:27<00:00,  1.00s/it]\n100%|██████████| 28/28 [00:27<00:00,  1.00it/s]",
  "metrics": {
    "predict_time": 39.024406853,
    "total_time": 50.758828
  },
  "output": [
    "https://replicate.delivery/yhqm/z7ggUr45f02EASGL3JGP9ujTp2iK7vfPNaoKetv2QVFNCMpmA/out-0.webp",
    "https://replicate.delivery/yhqm/g4BH4SItmdZsABXlRGr6sQoZk6292mzC6H5d7v7P2HyRgJ1E/out-1.webp",
    "https://replicate.delivery/yhqm/yCHuN4xwjwKiExSgoJPMOeRLdWHVu97GJLWbfJGSfykPCMpmA/out-2.webp",
    "https://replicate.delivery/yhqm/xeISZYToLazSA6eu7PPA6cGs7DeFg2AuMg9YqZKVeYwfIwkaC/out-3.webp"
  ],
  "started_at": "2024-08-20T14:54:24.307422Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/jt4kzbg0bnrm60che14asvhcdc",
    "cancel": "https://api.replicate.com/v1/predictions/jt4kzbg0bnrm60che14asvhcdc/cancel"
  },
  "version": "e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7"
}

Generated in

39.0 seconds

fofr/0_1-webp:e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7

Using seed: 35130
Prompt: A portrait photo of 0_1 as a charismatic female chef in a bustling kitchen, captured mid-action while cooking. She is wearing a crisp white chef's coat. She's also wearing a simple blue apron with the restaurant's logo embroidered on it. The apron strings are neatly tied around her waist. She has perfect eyes.
Behind her, there is a blurred background of a professional kitchen setting. Stainless steel appliances and cookware are visible, along with other chefs working in the background. On the wall, there's a chalkboard menu with the day's specials written in elegant handwriting.
txt2img mode
Using dev model
Loading LoRA weights
Ensuring enough disk space...
Free disk space: 9653500030976
Downloading weights
2024-08-20T14:54:24Z | INFO  | [ Initiating ] chunk_size=150M dest=/src/weights-cache/aa2152eb914fa84c url=https://replicate.delivery/yhqm/EgcoMuFe78SkBCR2lRD2Stf7KXN2tdWBJwwdl62xqNZEtWUTA/trained_model.tar
2024-08-20T14:54:25Z | INFO  | [ Complete ] dest=/src/weights-cache/aa2152eb914fa84c size="172 MB" total_elapsed=1.443s url=https://replicate.delivery/yhqm/EgcoMuFe78SkBCR2lRD2Stf7KXN2tdWBJwwdl62xqNZEtWUTA/trained_model.tar
b''
Downloaded weights in 1.466421127319336 seconds
LoRA weights loaded successfully
Token indices sequence length is longer than the specified maximum sequence length for this model (122 > 77). Running this sequence through the model will result in indexing errors
The following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ["background of a professional kitchen setting. stainless steel appliances and cookware are visible, along with other chefs working in the background. on the wall, there's a chalkboard menu with the day's specials written in elegant handwriting.", "background of a professional kitchen setting. stainless steel appliances and cookware are visible, along with other chefs working in the background. on the wall, there's a chalkboard menu with the day's specials written in elegant handwriting.", "background of a professional kitchen setting. stainless steel appliances and cookware are visible, along with other chefs working in the background. on the wall, there's a chalkboard menu with the day's specials written in elegant handwriting.", "background of a professional kitchen setting. stainless steel appliances and cookware are visible, along with other chefs working in the background. on the wall, there's a chalkboard menu with the day's specials written in elegant handwriting."]
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Prediction

Model

cca56cn6w1rm00che14vfcm5h8

Status

Succeeded

Source

Web

Hardware

H100

Total duration

41.4s

Created

10 months ago

Input

model: dev
prompt: A portrait photo of 0_1 as a confident female astronaut aboard the International Space Station, captured while floating in microgravity. She is wearing a blue NASA flight suit with patches on the shoulders. She's also wearing a communication headset with a microphone positioned near her mouth. A name tag on her chest reads "0_1" in bold letters. She has perfect eyes. Behind her, there is a blurred background of the space station's interior. Various scientific equipment and experiments can be seen attached to the walls. Through a small circular window, the curve of the Earth is visible against the blackness of space. Floating near her are several colorful spheres, possibly part of a science demonstration.
lora_scale: 0.9
num_outputs: 4
aspect_ratio: 3:4
output_format: webp
guidance_scale: 2.5
output_quality: 90
num_inference_steps: 28

{
  "model": "dev",
  "prompt": "A portrait photo of 0_1 as a confident female astronaut aboard the International Space Station, captured while floating in microgravity. She is wearing a blue NASA flight suit with patches on the shoulders. She's also wearing a communication headset with a microphone positioned near her mouth. A name tag on her chest reads \"0_1\" in bold letters. She has perfect eyes.\nBehind her, there is a blurred background of the space station's interior. Various scientific equipment and experiments can be seen attached to the walls. Through a small circular window, the curve of the Earth is visible against the blackness of space. Floating near her are several colorful spheres, possibly part of a science demonstration.",
  "lora_scale": 0.9,
  "num_outputs": 4,
  "aspect_ratio": "3:4",
  "output_format": "webp",
  "guidance_scale": 2.5,
  "output_quality": 90,
  "num_inference_steps": 28
}

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 fofr/0_1-webp using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "fofr/0_1-webp:e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7",
  {
    input: {
      model: "dev",
      prompt: "A portrait photo of 0_1 as a confident female astronaut aboard the International Space Station, captured while floating in microgravity. She is wearing a blue NASA flight suit with patches on the shoulders. She's also wearing a communication headset with a microphone positioned near her mouth. A name tag on her chest reads \"0_1\" in bold letters. She has perfect eyes.\nBehind her, there is a blurred background of the space station's interior. Various scientific equipment and experiments can be seen attached to the walls. Through a small circular window, the curve of the Earth is visible against the blackness of space. Floating near her are several colorful spheres, possibly part of a science demonstration.",
      lora_scale: 0.9,
      num_outputs: 4,
      aspect_ratio: "3:4",
      output_format: "webp",
      guidance_scale: 2.5,
      output_quality: 90,
      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

Import the client:

import replicate

Run fofr/0_1-webp using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "fofr/0_1-webp:e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7",
    input={
        "model": "dev",
        "prompt": "A portrait photo of 0_1 as a confident female astronaut aboard the International Space Station, captured while floating in microgravity. She is wearing a blue NASA flight suit with patches on the shoulders. She's also wearing a communication headset with a microphone positioned near her mouth. A name tag on her chest reads \"0_1\" in bold letters. She has perfect eyes.\nBehind her, there is a blurred background of the space station's interior. Various scientific equipment and experiments can be seen attached to the walls. Through a small circular window, the curve of the Earth is visible against the blackness of space. Floating near her are several colorful spheres, possibly part of a science demonstration.",
        "lora_scale": 0.9,
        "num_outputs": 4,
        "aspect_ratio": "3:4",
        "output_format": "webp",
        "guidance_scale": 2.5,
        "output_quality": 90,
        "num_inference_steps": 28
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Run fofr/0_1-webp 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": "fofr/0_1-webp:e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7",
    "input": {
      "model": "dev",
      "prompt": "A portrait photo of 0_1 as a confident female astronaut aboard the International Space Station, captured while floating in microgravity. She is wearing a blue NASA flight suit with patches on the shoulders. She\'s also wearing a communication headset with a microphone positioned near her mouth. A name tag on her chest reads \\"0_1\\" in bold letters. She has perfect eyes.\\nBehind her, there is a blurred background of the space station\'s interior. Various scientific equipment and experiments can be seen attached to the walls. Through a small circular window, the curve of the Earth is visible against the blackness of space. Floating near her are several colorful spheres, possibly part of a science demonstration.",
      "lora_scale": 0.9,
      "num_outputs": 4,
      "aspect_ratio": "3:4",
      "output_format": "webp",
      "guidance_scale": 2.5,
      "output_quality": 90,
      "num_inference_steps": 28
    }
  }' \
  https://api.replicate.com/v1/predictions

To 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 cog

If 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/fofr/0_1-webp@sha256:e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7 \
  -i 'model="dev"' \
  -i $'prompt="A portrait photo of 0_1 as a confident female astronaut aboard the International Space Station, captured while floating in microgravity. She is wearing a blue NASA flight suit with patches on the shoulders. She\'s also wearing a communication headset with a microphone positioned near her mouth. A name tag on her chest reads \\"0_1\\" in bold letters. She has perfect eyes.\\nBehind her, there is a blurred background of the space station\'s interior. Various scientific equipment and experiments can be seen attached to the walls. Through a small circular window, the curve of the Earth is visible against the blackness of space. Floating near her are several colorful spheres, possibly part of a science demonstration."' \
  -i 'lora_scale=0.9' \
  -i 'num_outputs=4' \
  -i 'aspect_ratio="3:4"' \
  -i 'output_format="webp"' \
  -i 'guidance_scale=2.5' \
  -i 'output_quality=90' \
  -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/fofr/0_1-webp@sha256:e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "model": "dev",
      "prompt": "A portrait photo of 0_1 as a confident female astronaut aboard the International Space Station, captured while floating in microgravity. She is wearing a blue NASA flight suit with patches on the shoulders. She\'s also wearing a communication headset with a microphone positioned near her mouth. A name tag on her chest reads \\"0_1\\" in bold letters. She has perfect eyes.\\nBehind her, there is a blurred background of the space station\'s interior. Various scientific equipment and experiments can be seen attached to the walls. Through a small circular window, the curve of the Earth is visible against the blackness of space. Floating near her are several colorful spheres, possibly part of a science demonstration.",
      "lora_scale": 0.9,
      "num_outputs": 4,
      "aspect_ratio": "3:4",
      "output_format": "webp",
      "guidance_scale": 2.5,
      "output_quality": 90,
      "num_inference_steps": 28
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

{
  "completed_at": "2024-08-20T14:56:42.091829Z",
  "created_at": "2024-08-20T14:56:00.736000Z",
  "data_removed": false,
  "error": null,
  "id": "cca56cn6w1rm00che14vfcm5h8",
  "input": {
    "model": "dev",
    "prompt": "A portrait photo of 0_1 as a confident female astronaut aboard the International Space Station, captured while floating in microgravity. She is wearing a blue NASA flight suit with patches on the shoulders. She's also wearing a communication headset with a microphone positioned near her mouth. A name tag on her chest reads \"0_1\" in bold letters. She has perfect eyes.\nBehind her, there is a blurred background of the space station's interior. Various scientific equipment and experiments can be seen attached to the walls. Through a small circular window, the curve of the Earth is visible against the blackness of space. Floating near her are several colorful spheres, possibly part of a science demonstration.",
    "lora_scale": 0.9,
    "num_outputs": 4,
    "aspect_ratio": "3:4",
    "output_format": "webp",
    "guidance_scale": 2.5,
    "output_quality": 90,
    "num_inference_steps": 28
  },
  "logs": "Using seed: 39343\nPrompt: A portrait photo of 0_1 as a confident female astronaut aboard the International Space Station, captured while floating in microgravity. She is wearing a blue NASA flight suit with patches on the shoulders. She's also wearing a communication headset with a microphone positioned near her mouth. A name tag on her chest reads \"0_1\" in bold letters. She has perfect eyes.\nBehind her, there is a blurred background of the space station's interior. Various scientific equipment and experiments can be seen attached to the walls. Through a small circular window, the curve of the Earth is visible against the blackness of space. Floating near her are several colorful spheres, possibly part of a science demonstration.\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nEnsuring enough disk space...\nFree disk space: 9448701767680\nDownloading weights\n2024-08-20T14:56:00Z | INFO  | [ Initiating ] chunk_size=150M dest=/src/weights-cache/aa2152eb914fa84c url=https://replicate.delivery/yhqm/EgcoMuFe78SkBCR2lRD2Stf7KXN2tdWBJwwdl62xqNZEtWUTA/trained_model.tar\n2024-08-20T14:56:02Z | INFO  | [ Complete ] dest=/src/weights-cache/aa2152eb914fa84c size=\"172 MB\" total_elapsed=1.429s url=https://replicate.delivery/yhqm/EgcoMuFe78SkBCR2lRD2Stf7KXN2tdWBJwwdl62xqNZEtWUTA/trained_model.tar\nb''\nDownloaded weights in 1.463416576385498 seconds\nLoRA weights loaded successfully\nToken indices sequence length is longer than the specified maximum sequence length for this model (140 > 77). Running this sequence through the model will result in indexing errors\nThe following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: [\"behind her, there is a blurred background of the space station's interior. various scientific equipment and experiments can be seen attached to the walls. through a small circular window, the curve of the earth is visible against the blackness of space. floating near her are several colorful spheres, possibly part of a science demonstration.\", \"behind her, there is a blurred background of the space station's interior. various scientific equipment and experiments can be seen attached to the walls. through a small circular window, the curve of the earth is visible against the blackness of space. floating near her are several colorful spheres, possibly part of a science demonstration.\", \"behind her, there is a blurred background of the space station's interior. various scientific equipment and experiments can be seen attached to the walls. through a small circular window, the curve of the earth is visible against the blackness of space. floating near her are several colorful spheres, possibly part of a science demonstration.\", \"behind her, there is a blurred background of the space station's interior. various scientific equipment and experiments can be seen attached to the walls. through a small circular window, the curve of the earth is visible against the blackness of space. floating near her are several colorful spheres, possibly part of a science demonstration.\"]\n  0%|          | 0/28 [00:00<?, ?it/s]\n  4%|▎         | 1/28 [00:01<00:28,  1.06s/it]\n  7%|▋         | 2/28 [00:01<00:23,  1.11it/s]\n 11%|█         | 3/28 [00:02<00:23,  1.06it/s]\n 14%|█▍        | 4/28 [00:03<00:23,  1.04it/s]\n 18%|█▊        | 5/28 [00:04<00:22,  1.03it/s]\n 21%|██▏       | 6/28 [00:05<00:21,  1.02it/s]\n 25%|██▌       | 7/28 [00:06<00:20,  1.01it/s]\n 29%|██▊       | 8/28 [00:07<00:19,  1.01it/s]\n 32%|███▏      | 9/28 [00:08<00:18,  1.01it/s]\n 36%|███▌      | 10/28 [00:09<00:17,  1.01it/s]\n 39%|███▉      | 11/28 [00:10<00:16,  1.01it/s]\n 43%|████▎     | 12/28 [00:11<00:15,  1.01it/s]\n 46%|████▋     | 13/28 [00:12<00:14,  1.01it/s]\n 50%|█████     | 14/28 [00:13<00:13,  1.01it/s]\n 54%|█████▎    | 15/28 [00:14<00:12,  1.01it/s]\n 57%|█████▋    | 16/28 [00:15<00:11,  1.01it/s]\n 61%|██████    | 17/28 [00:16<00:10,  1.01it/s]\n 64%|██████▍   | 18/28 [00:17<00:09,  1.01it/s]\n 68%|██████▊   | 19/28 [00:18<00:08,  1.01it/s]\n 71%|███████▏  | 20/28 [00:19<00:07,  1.01it/s]\n 75%|███████▌  | 21/28 [00:20<00:06,  1.01it/s]\n 79%|███████▊  | 22/28 [00:21<00:05,  1.01it/s]\n 82%|████████▏ | 23/28 [00:22<00:04,  1.01it/s]\n 86%|████████▌ | 24/28 [00:23<00:03,  1.00it/s]\n 89%|████████▉ | 25/28 [00:24<00:02,  1.00it/s]\n 93%|█████████▎| 26/28 [00:25<00:01,  1.00it/s]\n 96%|█████████▋| 27/28 [00:26<00:00,  1.00it/s]\n100%|██████████| 28/28 [00:27<00:00,  1.00it/s]\n100%|██████████| 28/28 [00:27<00:00,  1.01it/s]",
  "metrics": {
    "predict_time": 41.144997168,
    "total_time": 41.355829
  },
  "output": [
    "https://replicate.delivery/yhqm/zCR7Nd8ctTKjPpKo6frylnS2v87gpniLrBumjZJ58F5UBTqJA/out-0.webp",
    "https://replicate.delivery/yhqm/Oj52v7Lj45plJxzVKwK7ckJOygsJRXkAf5qeU8oE6lcpCmUTA/out-1.webp",
    "https://replicate.delivery/yhqm/lphTn5l7UhoTO1PZnDc4Q0ZDHrjFzcSsdd0u0cdkqpTqgJ1E/out-2.webp",
    "https://replicate.delivery/yhqm/F5OSomjxkBplEBwfBeZJmtuz0ywEGOopCPmjruhGlIqqCmUTA/out-3.webp"
  ],
  "started_at": "2024-08-20T14:56:00.946832Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/cca56cn6w1rm00che14vfcm5h8",
    "cancel": "https://api.replicate.com/v1/predictions/cca56cn6w1rm00che14vfcm5h8/cancel"
  },
  "version": "e927742a5f430e7e36f3a646ced840cebb4c59e00e1bd1993e068a7f97a85fd7"
}

Generated in

41.1 seconds