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Input
Run this model in Node.js with one line of code:
npm install replicateREPLICATE_API_TOKEN environment variableexport 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 kuprel/min-dalle using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"kuprel/min-dalle:c1fca4bef52afc0c3a556060df13d7d7c429a1310feeedbb5c3f92b7002822de",
{
input: {
text: "Dali painting of WALL·E",
top_k: 64,
seamless: false,
grid_size: 5,
save_as_png: false,
temperature: 4,
progressive_outputs: true,
supercondition_factor: 16
}
}
);
console.log(output);To learn more, take a look at the guide on getting started with Node.js.
pip install replicateREPLICATE_API_TOKEN environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
import replicateRun kuprel/min-dalle using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"kuprel/min-dalle:c1fca4bef52afc0c3a556060df13d7d7c429a1310feeedbb5c3f92b7002822de",
input={
"text": "Dali painting of WALL·E",
"top_k": 64,
"seamless": False,
"grid_size": 5,
"save_as_png": False,
"temperature": 4,
"progressive_outputs": True,
"supercondition_factor": 16
}
)
# The kuprel/min-dalle model can stream output as it's running.
# The predict method returns an iterator, and you can iterate over that output.
for item in output:
# https://replicate.com/kuprel/min-dalle/api#output-schema
print(item)To learn more, take a look at the guide on getting started with Python.
REPLICATE_API_TOKEN environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run kuprel/min-dalle 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": "c1fca4bef52afc0c3a556060df13d7d7c429a1310feeedbb5c3f92b7002822de",
"input": {
"text": "Dali painting of WALL·E",
"top_k": 64,
"seamless": false,
"grid_size": 5,
"save_as_png": false,
"temperature": 4,
"progressive_outputs": true,
"supercondition_factor": 16
}
}' \
https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
brew install cogIf you don’t have Homebrew, there are other installation options available.
Pull and run kuprel/min-dalle using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/kuprel/min-dalle@sha256:c1fca4bef52afc0c3a556060df13d7d7c429a1310feeedbb5c3f92b7002822de \
-i 'text="Dali painting of WALL·E"' \
-i 'top_k=64' \
-i 'seamless=false' \
-i 'grid_size=5' \
-i 'save_as_png=false' \
-i 'temperature=4' \
-i 'progressive_outputs=true' \
-i 'supercondition_factor=16'To learn more, take a look at the Cog documentation.
Pull and run kuprel/min-dalle using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/kuprel/min-dalle@sha256:c1fca4bef52afc0c3a556060df13d7d7c429a1310feeedbb5c3f92b7002822decurl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "text": "Dali painting of WALL·E", "top_k": 64, "seamless": false, "grid_size": 5, "save_as_png": false, "temperature": 4, "progressive_outputs": true, "supercondition_factor": 16 } }' \ http://localhost:5000/predictions
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Output
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