Prediction
lucataco/open-dalle-v1.1:1c7d4c8dec39c7306df7794b28419078cb9d18b9213ab1c21fdc46a1deca0144ID
5dgh3d3brw5b2ey6gy2dirihpy
Status
Succeeded
Source
Web
Hardware
A40 (Large)
Total duration
Created
Input
- width
- 1024
- height
- 1024
- prompt
- (impressionistic realism by csybgh), a 50 something male, working in banking, very short dyed dark curly balding hair, Afro-Asiatic ancestry, talks a lot but listens poorly, stuck in the past, wearing a suit, he has a certain charm, bronze skintone, sitting in a bar at night, he is smoking and feeling cool, drunk on plum wine, masterpiece, 8k, hyper detailed, smokey ambiance, perfect hands AND fingers
- scheduler
- KarrasDPM
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- negative_prompt
- worst quality, low quality
- prompt_strength
- 0.8
- num_inference_steps
- 60
{
"width": 1024,
"height": 1024,
"prompt": "(impressionistic realism by csybgh), a 50 something male, working in banking, very short dyed dark curly balding hair, Afro-Asiatic ancestry, talks a lot but listens poorly, stuck in the past, wearing a suit, he has a certain charm, bronze skintone, sitting in a bar at night, he is smoking and feeling cool, drunk on plum wine, masterpiece, 8k, hyper detailed, smokey ambiance, perfect hands AND fingers",
"scheduler": "KarrasDPM",
"num_outputs": 1,
"guidance_scale": 7.5,
"apply_watermark": true,
"negative_prompt": "worst quality, low quality",
"prompt_strength": 0.8,
"num_inference_steps": 60
}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 lucataco/open-dalle-v1.1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"lucataco/open-dalle-v1.1:1c7d4c8dec39c7306df7794b28419078cb9d18b9213ab1c21fdc46a1deca0144",
{
input: {
width: 1024,
height: 1024,
prompt: "(impressionistic realism by csybgh), a 50 something male, working in banking, very short dyed dark curly balding hair, Afro-Asiatic ancestry, talks a lot but listens poorly, stuck in the past, wearing a suit, he has a certain charm, bronze skintone, sitting in a bar at night, he is smoking and feeling cool, drunk on plum wine, masterpiece, 8k, hyper detailed, smokey ambiance, perfect hands AND fingers",
scheduler: "KarrasDPM",
num_outputs: 1,
guidance_scale: 7.5,
apply_watermark: true,
negative_prompt: "worst quality, low quality",
prompt_strength: 0.8,
num_inference_steps: 60
}
}
);
// 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 lucataco/open-dalle-v1.1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"lucataco/open-dalle-v1.1:1c7d4c8dec39c7306df7794b28419078cb9d18b9213ab1c21fdc46a1deca0144",
input={
"width": 1024,
"height": 1024,
"prompt": "(impressionistic realism by csybgh), a 50 something male, working in banking, very short dyed dark curly balding hair, Afro-Asiatic ancestry, talks a lot but listens poorly, stuck in the past, wearing a suit, he has a certain charm, bronze skintone, sitting in a bar at night, he is smoking and feeling cool, drunk on plum wine, masterpiece, 8k, hyper detailed, smokey ambiance, perfect hands AND fingers",
"scheduler": "KarrasDPM",
"num_outputs": 1,
"guidance_scale": 7.5,
"apply_watermark": True,
"negative_prompt": "worst quality, low quality",
"prompt_strength": 0.8,
"num_inference_steps": 60
}
)
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 lucataco/open-dalle-v1.1 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": "lucataco/open-dalle-v1.1:1c7d4c8dec39c7306df7794b28419078cb9d18b9213ab1c21fdc46a1deca0144",
"input": {
"width": 1024,
"height": 1024,
"prompt": "(impressionistic realism by csybgh), a 50 something male, working in banking, very short dyed dark curly balding hair, Afro-Asiatic ancestry, talks a lot but listens poorly, stuck in the past, wearing a suit, he has a certain charm, bronze skintone, sitting in a bar at night, he is smoking and feeling cool, drunk on plum wine, masterpiece, 8k, hyper detailed, smokey ambiance, perfect hands AND fingers",
"scheduler": "KarrasDPM",
"num_outputs": 1,
"guidance_scale": 7.5,
"apply_watermark": true,
"negative_prompt": "worst quality, low quality",
"prompt_strength": 0.8,
"num_inference_steps": 60
}
}' \
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/lucataco/open-dalle-v1.1@sha256:1c7d4c8dec39c7306df7794b28419078cb9d18b9213ab1c21fdc46a1deca0144 \
-i 'width=1024' \
-i 'height=1024' \
-i 'prompt="(impressionistic realism by csybgh), a 50 something male, working in banking, very short dyed dark curly balding hair, Afro-Asiatic ancestry, talks a lot but listens poorly, stuck in the past, wearing a suit, he has a certain charm, bronze skintone, sitting in a bar at night, he is smoking and feeling cool, drunk on plum wine, masterpiece, 8k, hyper detailed, smokey ambiance, perfect hands AND fingers"' \
-i 'scheduler="KarrasDPM"' \
-i 'num_outputs=1' \
-i 'guidance_scale=7.5' \
-i 'apply_watermark=true' \
-i 'negative_prompt="worst quality, low quality"' \
-i 'prompt_strength=0.8' \
-i 'num_inference_steps=60'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/lucataco/open-dalle-v1.1@sha256:1c7d4c8dec39c7306df7794b28419078cb9d18b9213ab1c21fdc46a1deca0144curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 1024, "height": 1024, "prompt": "(impressionistic realism by csybgh), a 50 something male, working in banking, very short dyed dark curly balding hair, Afro-Asiatic ancestry, talks a lot but listens poorly, stuck in the past, wearing a suit, he has a certain charm, bronze skintone, sitting in a bar at night, he is smoking and feeling cool, drunk on plum wine, masterpiece, 8k, hyper detailed, smokey ambiance, perfect hands AND fingers", "scheduler": "KarrasDPM", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "negative_prompt": "worst quality, low quality", "prompt_strength": 0.8, "num_inference_steps": 60 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Output
{
"completed_at": "2023-12-27T06:52:13.952725Z",
"created_at": "2023-12-27T06:51:59.727364Z",
"data_removed": false,
"error": null,
"id": "5dgh3d3brw5b2ey6gy2dirihpy",
"input": {
"width": 1024,
"height": 1024,
"prompt": "(impressionistic realism by csybgh), a 50 something male, working in banking, very short dyed dark curly balding hair, Afro-Asiatic ancestry, talks a lot but listens poorly, stuck in the past, wearing a suit, he has a certain charm, bronze skintone, sitting in a bar at night, he is smoking and feeling cool, drunk on plum wine, masterpiece, 8k, hyper detailed, smokey ambiance, perfect hands AND fingers",
"scheduler": "KarrasDPM",
"num_outputs": 1,
"guidance_scale": 7.5,
"apply_watermark": true,
"negative_prompt": "worst quality, low quality",
"prompt_strength": 0.8,
"num_inference_steps": 60
},
"logs": "Using seed: 416690887\nPrompt: (impressionistic realism by csybgh), a 50 something male, working in banking, very short dyed dark curly balding hair, Afro-Asiatic ancestry, talks a lot but listens poorly, stuck in the past, wearing a suit, he has a certain charm, bronze skintone, sitting in a bar at night, he is smoking and feeling cool, drunk on plum wine, masterpiece, 8k, hyper detailed, smokey ambiance, perfect hands AND fingers\ntxt2img mode\nToken indices sequence length is longer than the specified maximum sequence length for this model (101 > 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: ['feeling cool, drunk on plum wine, masterpiece, 8 k, hyper detailed, smokey ambiance, perfect hands and fingers']\nToken indices sequence length is longer than the specified maximum sequence length for this model (101 > 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: ['feeling cool, drunk on plum wine, masterpiece, 8 k, hyper detailed, smokey ambiance, perfect hands and fingers']\n 0%| | 0/60 [00:00<?, ?it/s]\n 2%|▏ | 1/60 [00:00<00:11, 4.94it/s]\n 5%|▌ | 3/60 [00:00<00:09, 6.15it/s]\n 7%|▋ | 4/60 [00:00<00:09, 5.68it/s]\n 8%|▊ | 5/60 [00:00<00:10, 5.41it/s]\n 10%|█ | 6/60 [00:01<00:10, 5.24it/s]\n 12%|█▏ | 7/60 [00:01<00:10, 5.14it/s]\n 13%|█▎ | 8/60 [00:01<00:10, 5.08it/s]\n 15%|█▌ | 9/60 [00:01<00:10, 5.04it/s]\n 17%|█▋ | 10/60 [00:01<00:09, 5.00it/s]\n 18%|█▊ | 11/60 [00:02<00:09, 4.97it/s]\n 20%|██ | 12/60 [00:02<00:09, 4.95it/s]\n 22%|██▏ | 13/60 [00:02<00:09, 4.94it/s]\n 23%|██▎ | 14/60 [00:02<00:09, 4.93it/s]\n 25%|██▌ | 15/60 [00:02<00:09, 4.93it/s]\n 27%|██▋ | 16/60 [00:03<00:08, 4.92it/s]\n 28%|██▊ | 17/60 [00:03<00:08, 4.92it/s]\n 30%|███ | 18/60 [00:03<00:08, 4.92it/s]\n 32%|███▏ | 19/60 [00:03<00:08, 4.91it/s]\n 33%|███▎ | 20/60 [00:03<00:08, 4.91it/s]\n 35%|███▌ | 21/60 [00:04<00:07, 4.92it/s]\n 37%|███▋ | 22/60 [00:04<00:07, 4.92it/s]\n 38%|███▊ | 23/60 [00:04<00:07, 4.92it/s]\n 40%|████ | 24/60 [00:04<00:07, 4.91it/s]\n 42%|████▏ | 25/60 [00:04<00:07, 4.91it/s]\n 43%|████▎ | 26/60 [00:05<00:06, 4.91it/s]\n 45%|████▌ | 27/60 [00:05<00:06, 4.91it/s]\n 47%|████▋ | 28/60 [00:05<00:06, 4.87it/s]\n 48%|████▊ | 29/60 [00:05<00:06, 4.85it/s]\n 50%|█████ | 30/60 [00:05<00:06, 4.87it/s]\n 52%|█████▏ | 31/60 [00:06<00:05, 4.88it/s]\n 53%|█████▎ | 32/60 [00:06<00:05, 4.88it/s]\n 55%|█████▌ | 33/60 [00:06<00:05, 4.89it/s]\n 57%|█████▋ | 34/60 [00:06<00:05, 4.90it/s]\n 58%|█████▊ | 35/60 [00:07<00:05, 4.90it/s]\n 60%|██████ | 36/60 [00:07<00:04, 4.90it/s]\n 62%|██████▏ | 37/60 [00:07<00:04, 4.90it/s]\n 63%|██████▎ | 38/60 [00:07<00:04, 4.90it/s]\n 65%|██████▌ | 39/60 [00:07<00:04, 4.90it/s]\n 67%|██████▋ | 40/60 [00:08<00:04, 4.91it/s]\n 68%|██████▊ | 41/60 [00:08<00:03, 4.90it/s]\n 70%|███████ | 42/60 [00:08<00:03, 4.90it/s]\n 72%|███████▏ | 43/60 [00:08<00:03, 4.90it/s]\n 73%|███████▎ | 44/60 [00:08<00:03, 4.89it/s]\n 75%|███████▌ | 45/60 [00:09<00:03, 4.89it/s]\n 77%|███████▋ | 46/60 [00:09<00:02, 4.90it/s]\n 78%|███████▊ | 47/60 [00:09<00:02, 4.90it/s]\n 80%|████████ | 48/60 [00:09<00:02, 4.89it/s]\n 82%|████████▏ | 49/60 [00:09<00:02, 4.89it/s]\n 83%|████████▎ | 50/60 [00:10<00:02, 4.89it/s]\n 85%|████████▌ | 51/60 [00:10<00:01, 4.90it/s]\n 87%|████████▋ | 52/60 [00:10<00:01, 4.89it/s]\n 88%|████████▊ | 53/60 [00:10<00:01, 4.89it/s]\n 90%|█████████ | 54/60 [00:10<00:01, 4.89it/s]\n 92%|█████████▏| 55/60 [00:11<00:01, 4.89it/s]\n 93%|█████████▎| 56/60 [00:11<00:00, 4.89it/s]\n 95%|█████████▌| 57/60 [00:11<00:00, 4.90it/s]\n 97%|█████████▋| 58/60 [00:11<00:00, 4.89it/s]\n 98%|█████████▊| 59/60 [00:11<00:00, 4.90it/s]\n100%|██████████| 60/60 [00:12<00:00, 4.90it/s]\n100%|██████████| 60/60 [00:12<00:00, 4.95it/s]",
"metrics": {
"predict_time": 14.19093,
"total_time": 14.225361
},
"output": [
"https://replicate.delivery/pbxt/xFUXm1cNnlKsB1Mb5Hzz5yHEVIAdXEO7g3TZAPxfGZrO3LDJA/out-0.png"
],
"started_at": "2023-12-27T06:51:59.761795Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/5dgh3d3brw5b2ey6gy2dirihpy",
"cancel": "https://api.replicate.com/v1/predictions/5dgh3d3brw5b2ey6gy2dirihpy/cancel"
},
"version": "1c7d4c8dec39c7306df7794b28419078cb9d18b9213ab1c21fdc46a1deca0144"
}Generated in
Using seed: 416690887
Prompt: (impressionistic realism by csybgh), a 50 something male, working in banking, very short dyed dark curly balding hair, Afro-Asiatic ancestry, talks a lot but listens poorly, stuck in the past, wearing a suit, he has a certain charm, bronze skintone, sitting in a bar at night, he is smoking and feeling cool, drunk on plum wine, masterpiece, 8k, hyper detailed, smokey ambiance, perfect hands AND fingers
txt2img mode
Token indices sequence length is longer than the specified maximum sequence length for this model (101 > 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: ['feeling cool, drunk on plum wine, masterpiece, 8 k, hyper detailed, smokey ambiance, perfect hands and fingers']
Token indices sequence length is longer than the specified maximum sequence length for this model (101 > 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: ['feeling cool, drunk on plum wine, masterpiece, 8 k, hyper detailed, smokey ambiance, perfect hands and fingers']
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