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camenduru /dynami-crafter-576x1024:e79ff8d0
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";
import fs from "node:fs";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});
Run camenduru/dynami-crafter-576x1024 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"camenduru/dynami-crafter-576x1024:e79ff8d01e81cbd90acfa1df4f209f637da2c68307891d77a6e4227f4ec350f1",
{
input: {
i2v_eta: 1,
i2v_seed: 123,
i2v_steps: 50,
i2v_motion: 4,
i2v_cfg_scale: 7.5,
i2v_input_text: "rocket launches",
i2v_input_image: "https://replicate.delivery/pbxt/KLre7ADFhbmP9FJh3soDttYBSeyNdE4dPmR8G2TL0YFRqk6L/girl07.png"
}
}
);
// To access the file URL:
console.log(output.url()); //=> "http://example.com"
// To write the file to disk:
fs.writeFile("my-image.png", 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 camenduru/dynami-crafter-576x1024 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"camenduru/dynami-crafter-576x1024:e79ff8d01e81cbd90acfa1df4f209f637da2c68307891d77a6e4227f4ec350f1",
input={
"i2v_eta": 1,
"i2v_seed": 123,
"i2v_steps": 50,
"i2v_motion": 4,
"i2v_cfg_scale": 7.5,
"i2v_input_text": "rocket launches",
"i2v_input_image": "https://replicate.delivery/pbxt/KLre7ADFhbmP9FJh3soDttYBSeyNdE4dPmR8G2TL0YFRqk6L/girl07.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 camenduru/dynami-crafter-576x1024 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": "camenduru/dynami-crafter-576x1024:e79ff8d01e81cbd90acfa1df4f209f637da2c68307891d77a6e4227f4ec350f1",
"input": {
"i2v_eta": 1,
"i2v_seed": 123,
"i2v_steps": 50,
"i2v_motion": 4,
"i2v_cfg_scale": 7.5,
"i2v_input_text": "rocket launches",
"i2v_input_image": "https://replicate.delivery/pbxt/KLre7ADFhbmP9FJh3soDttYBSeyNdE4dPmR8G2TL0YFRqk6L/girl07.png"
}
}' \
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": "2024-02-06T03:56:40.012383Z",
"created_at": "2024-02-06T03:49:03.233811Z",
"data_removed": false,
"error": null,
"id": "rskji3zbcq7ndpep3zslvj6sqa",
"input": {
"i2v_eta": 1,
"i2v_seed": 123,
"i2v_steps": 50,
"i2v_motion": 4,
"i2v_cfg_scale": 7.5,
"i2v_input_text": "rocket launches",
"i2v_input_image": "https://replicate.delivery/pbxt/KLre7ADFhbmP9FJh3soDttYBSeyNdE4dPmR8G2TL0YFRqk6L/girl07.png"
},
"logs": "Seed set to 123\nstart: rocket launches 2024-02-06 03:52:52\n/root/.pyenv/versions/3.10.13/lib/python3.10/site-packages/torchvision/transforms/functional.py:1603: UserWarning: The default value of the antialias parameter of all the resizing transforms (Resize(), RandomResizedCrop(), etc.) will change from None to True in v0.17, in order to be consistent across the PIL and Tensor backends. To suppress this warning, directly pass antialias=True (recommended, future default), antialias=None (current default, which means False for Tensors and True for PIL), or antialias=False (only works on Tensors - PIL will still use antialiasing). This also applies if you are using the inference transforms from the models weights: update the call to weights.transforms(antialias=True).\nwarnings.warn(",
"metrics": {
"predict_time": 228.04025,
"total_time": 456.778572
},
"output": "https://replicate.delivery/pbxt/fWnOmFsM4i1fPkEk4nKx0yx440nKqSnFleb7etsPE1f6ef6JJA/output.mp4",
"started_at": "2024-02-06T03:52:51.972133Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/rskji3zbcq7ndpep3zslvj6sqa",
"cancel": "https://api.replicate.com/v1/predictions/rskji3zbcq7ndpep3zslvj6sqa/cancel"
},
"version": "e79ff8d01e81cbd90acfa1df4f209f637da2c68307891d77a6e4227f4ec350f1"
}
Seed set to 123
start: rocket launches 2024-02-06 03:52:52
/root/.pyenv/versions/3.10.13/lib/python3.10/site-packages/torchvision/transforms/functional.py:1603: UserWarning: The default value of the antialias parameter of all the resizing transforms (Resize(), RandomResizedCrop(), etc.) will change from None to True in v0.17, in order to be consistent across the PIL and Tensor backends. To suppress this warning, directly pass antialias=True (recommended, future default), antialias=None (current default, which means False for Tensors and True for PIL), or antialias=False (only works on Tensors - PIL will still use antialiasing). This also applies if you are using the inference transforms from the models weights: update the call to weights.transforms(antialias=True).
warnings.warn(