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methexis-inc /img2prompt:50adaf2d
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 methexis-inc/img2prompt using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"methexis-inc/img2prompt:50adaf2d3ad20a6f911a8a9e3ccf777b263b8596fbd2c8fc26e8888f8a0edbb5",
{
input: {
image: "https://replicate.delivery/mgxm/a3daf048-9f89-472e-af91-302733090760/out-3.png"
}
}
);
console.log(output);
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 methexis-inc/img2prompt using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"methexis-inc/img2prompt:50adaf2d3ad20a6f911a8a9e3ccf777b263b8596fbd2c8fc26e8888f8a0edbb5",
input={
"image": "https://replicate.delivery/mgxm/a3daf048-9f89-472e-af91-302733090760/out-3.png"
}
)
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 methexis-inc/img2prompt 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": "50adaf2d3ad20a6f911a8a9e3ccf777b263b8596fbd2c8fc26e8888f8a0edbb5",
"input": {
"image": "https://replicate.delivery/mgxm/a3daf048-9f89-472e-af91-302733090760/out-3.png"
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
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/methexis-inc/img2prompt@sha256:50adaf2d3ad20a6f911a8a9e3ccf777b263b8596fbd2c8fc26e8888f8a0edbb5 \
-i 'image="https://replicate.delivery/mgxm/a3daf048-9f89-472e-af91-302733090760/out-3.png"'
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/methexis-inc/img2prompt@sha256:50adaf2d3ad20a6f911a8a9e3ccf777b263b8596fbd2c8fc26e8888f8a0edbb5
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "image": "https://replicate.delivery/mgxm/a3daf048-9f89-472e-af91-302733090760/out-3.png" } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
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Output
{
"completed_at": "2022-08-25T00:28:07.690797Z",
"created_at": "2022-08-25T00:27:39.201750Z",
"data_removed": false,
"error": null,
"id": "cq7qunqws5fbzjx3crvr2cel5a",
"input": {
"image": "https://replicate.delivery/mgxm/a3daf048-9f89-472e-af91-302733090760/out-3.png"
},
"logs": "Interrogating with ViT-L/14...",
"metrics": {
"predict_time": 28.300395,
"total_time": 28.489047
},
"output": "\n\na painting of a mountain landscape with a river running through it, a matte painting by Asher Brown Durand, cgsociety, hudson river school, matte painting, oil on canvas, terragen",
"started_at": "2022-08-25T00:27:39.390402Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/cq7qunqws5fbzjx3crvr2cel5a",
"cancel": "https://api.replicate.com/v1/predictions/cq7qunqws5fbzjx3crvr2cel5a/cancel"
},
"version": "50adaf2d3ad20a6f911a8a9e3ccf777b263b8596fbd2c8fc26e8888f8a0edbb5"
}
Interrogating with ViT-L/14...