Cold

ResNet Fine-Tuned on 37 dog & cat breeds

Public

184 runs

CPU

Run with an API

Pricing

Playground API Examples README Versions

Prediction

mopineyro/resnet_breeds_finetuned:9322649a726f17824c34d5d8dadf73c6c10473269e744f85444ba21b97727ab8

Model

mopineyro/resnet_breeds_finetuned:9322649a

sb45y3me3srge0cf29fbnxsbk0

Status

Succeeded

Source

Web

Hardware

CPU

Total duration

1m 40s

Created

over 1 year ago

Input

image: https://pub-4dfebb4424b1446080a05f71c33148f9.r2.dev/pug.png

{
  "image": "https://pub-4dfebb4424b1446080a05f71c33148f9.r2.dev/pug.png"
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run mopineyro/resnet_breeds_finetuned using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "mopineyro/resnet_breeds_finetuned:9322649a726f17824c34d5d8dadf73c6c10473269e744f85444ba21b97727ab8",
  {
    input: {
      image: "https://pub-4dfebb4424b1446080a05f71c33148f9.r2.dev/pug.png"
    }
  }
);

console.log(output);

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

Install Replicate’s Python client library:

pip install replicate

Import the client:

import replicate

Run mopineyro/resnet_breeds_finetuned using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "mopineyro/resnet_breeds_finetuned:9322649a726f17824c34d5d8dadf73c6c10473269e744f85444ba21b97727ab8",
    input={
        "image": "https://pub-4dfebb4424b1446080a05f71c33148f9.r2.dev/pug.png"
    }
)

print(output)

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

Run mopineyro/resnet_breeds_finetuned 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": "mopineyro/resnet_breeds_finetuned:9322649a726f17824c34d5d8dadf73c6c10473269e744f85444ba21b97727ab8",
    "input": {
      "image": "https://pub-4dfebb4424b1446080a05f71c33148f9.r2.dev/pug.png"
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

pug

Generated in

0.8 seconds

Tweak it Share Report

Prediction

mopineyro/resnet_breeds_finetuned:92c8bf4383777991823c24a33902528c2feffe18278ab1da3038bd2b0f650bd8

Model

mopineyro/resnet_breeds_finetuned:92c8bf43

eb8vqpv7vhrg80cf29t89wxxp4

Status

Succeeded

Source

Web

Hardware

CPU

Total duration

4m 48s

Created

over 1 year ago

Input

image_file

{
  "image_file": "https://replicate.delivery/pbxt/Ko0bQmqBRfDK48RIl24BQULbSGFuowa1C912KfNEgu8uYrSJ/beagle.png"
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run mopineyro/resnet_breeds_finetuned using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "mopineyro/resnet_breeds_finetuned:92c8bf4383777991823c24a33902528c2feffe18278ab1da3038bd2b0f650bd8",
  {
    input: {
      image_file: "https://replicate.delivery/pbxt/Ko0bQmqBRfDK48RIl24BQULbSGFuowa1C912KfNEgu8uYrSJ/beagle.png"
    }
  }
);

console.log(output);

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

Install Replicate’s Python client library:

pip install replicate

Import the client:

import replicate

Run mopineyro/resnet_breeds_finetuned using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "mopineyro/resnet_breeds_finetuned:92c8bf4383777991823c24a33902528c2feffe18278ab1da3038bd2b0f650bd8",
    input={
        "image_file": "https://replicate.delivery/pbxt/Ko0bQmqBRfDK48RIl24BQULbSGFuowa1C912KfNEgu8uYrSJ/beagle.png"
    }
)

print(output)

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

Run mopineyro/resnet_breeds_finetuned 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": "mopineyro/resnet_breeds_finetuned:92c8bf4383777991823c24a33902528c2feffe18278ab1da3038bd2b0f650bd8",
    "input": {
      "image_file": "https://replicate.delivery/pbxt/Ko0bQmqBRfDK48RIl24BQULbSGFuowa1C912KfNEgu8uYrSJ/beagle.png"
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

beagle

Generated in

4.5 seconds

Tweak it Share Report

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Output

Prediction

Input

Output

Logs (sb45y3me3srge0cf29fbnxsbk0)

Logs (eb8vqpv7vhrg80cf29t89wxxp4)