Prediction

ID

7aaul7xqlfcjheh6zss57aa2vy

Status

Succeeded

Source

Web

Hardware

–

Total duration

1.2s

Created

over 3 years ago

Input

input

{
  "input": "https://replicate.delivery/mgxm/2736d2b2-0be9-4770-9e9f-456fafb4312c/mnist.png"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run vganapati/mnist-classification using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "vganapati/mnist-classification:f3d94d920835d9ae085f0f0eb2ed8ff9f9771554e382af11e83cd79f1a646cb7",
  {
    input: {
      input: "https://replicate.delivery/mgxm/2736d2b2-0be9-4770-9e9f-456fafb4312c/mnist.png"
    }
  }
);

console.log(output);

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

pip install replicate

Import the client:

import replicate

Run vganapati/mnist-classification using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "vganapati/mnist-classification:f3d94d920835d9ae085f0f0eb2ed8ff9f9771554e382af11e83cd79f1a646cb7",
    input={
        "input": "https://replicate.delivery/mgxm/2736d2b2-0be9-4770-9e9f-456fafb4312c/mnist.png"
    }
)

# The vganapati/mnist-classification 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/vganapati/mnist-classification/api#output-schema
    print(item)

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

Run vganapati/mnist-classification 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": "vganapati/mnist-classification:f3d94d920835d9ae085f0f0eb2ed8ff9f9771554e382af11e83cd79f1a646cb7",
    "input": {
      "input": "https://replicate.delivery/mgxm/2736d2b2-0be9-4770-9e9f-456fafb4312c/mnist.png"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

5

Generated in

0.7 seconds

vganapati/mnist-classification:f3d94d920835d9ae085f0f0eb2ed8ff9f9771554e382af11e83cd79f1a646cb7

Prediction

Model

ID

2hrxlop4wjhk5a6qvs736s4n5q

Status

Succeeded

Source

Web

Hardware

–

Total duration

1.0s

Created

over 3 years ago

Input

input

{
  "input": "https://replicate.delivery/mgxm/2981468f-ba45-44ef-b67f-9daf22c3845a/mnist.png"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run vganapati/mnist-classification using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "vganapati/mnist-classification:f3d94d920835d9ae085f0f0eb2ed8ff9f9771554e382af11e83cd79f1a646cb7",
  {
    input: {
      input: "https://replicate.delivery/mgxm/2981468f-ba45-44ef-b67f-9daf22c3845a/mnist.png"
    }
  }
);

console.log(output);

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

pip install replicate

Import the client:

import replicate

Run vganapati/mnist-classification using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "vganapati/mnist-classification:f3d94d920835d9ae085f0f0eb2ed8ff9f9771554e382af11e83cd79f1a646cb7",
    input={
        "input": "https://replicate.delivery/mgxm/2981468f-ba45-44ef-b67f-9daf22c3845a/mnist.png"
    }
)

# The vganapati/mnist-classification 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/vganapati/mnist-classification/api#output-schema
    print(item)

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

Run vganapati/mnist-classification 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": "vganapati/mnist-classification:f3d94d920835d9ae085f0f0eb2ed8ff9f9771554e382af11e83cd79f1a646cb7",
    "input": {
      "input": "https://replicate.delivery/mgxm/2981468f-ba45-44ef-b67f-9daf22c3845a/mnist.png"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

3

Generated in

0.6 seconds

vganapati/mnist-classification:f3d94d920835d9ae085f0f0eb2ed8ff9f9771554e382af11e83cd79f1a646cb7

Prediction

Model

ID

kvlpgamjjngmjniq5gx24jboki

Status

Succeeded

Source

Web

Hardware

–

Total duration

1.2s

Created

over 3 years ago

Input

input

{
  "input": "https://replicate.delivery/mgxm/b6d62992-3b1b-4c88-bff1-e5337335afa7/mnist.png"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run vganapati/mnist-classification using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "vganapati/mnist-classification:f3d94d920835d9ae085f0f0eb2ed8ff9f9771554e382af11e83cd79f1a646cb7",
  {
    input: {
      input: "https://replicate.delivery/mgxm/b6d62992-3b1b-4c88-bff1-e5337335afa7/mnist.png"
    }
  }
);

console.log(output);

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

pip install replicate

Import the client:

import replicate

Run vganapati/mnist-classification using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "vganapati/mnist-classification:f3d94d920835d9ae085f0f0eb2ed8ff9f9771554e382af11e83cd79f1a646cb7",
    input={
        "input": "https://replicate.delivery/mgxm/b6d62992-3b1b-4c88-bff1-e5337335afa7/mnist.png"
    }
)

# The vganapati/mnist-classification 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/vganapati/mnist-classification/api#output-schema
    print(item)

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

Run vganapati/mnist-classification 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": "vganapati/mnist-classification:f3d94d920835d9ae085f0f0eb2ed8ff9f9771554e382af11e83cd79f1a646cb7",
    "input": {
      "input": "https://replicate.delivery/mgxm/b6d62992-3b1b-4c88-bff1-e5337335afa7/mnist.png"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

1

Generated in

0.7 seconds

vganapati/mnist-classification:f3d94d920835d9ae085f0f0eb2ed8ff9f9771554e382af11e83cd79f1a646cb7

Prediction

Model

ID

dv3uexahjncx3nqyjpo7fwtp44

Status

Succeeded

Source

Web

Hardware

–

Total duration

29.6s

Created

over 3 years ago

Input

input

{
  "input": "https://replicate.delivery/mgxm/e48d7acb-260c-4c6e-a5e5-582e4b5a3274/mnist.png"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run vganapati/mnist-classification using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "vganapati/mnist-classification:f3d94d920835d9ae085f0f0eb2ed8ff9f9771554e382af11e83cd79f1a646cb7",
  {
    input: {
      input: "https://replicate.delivery/mgxm/e48d7acb-260c-4c6e-a5e5-582e4b5a3274/mnist.png"
    }
  }
);

console.log(output);

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

pip install replicate

Import the client:

import replicate

Run vganapati/mnist-classification using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "vganapati/mnist-classification:f3d94d920835d9ae085f0f0eb2ed8ff9f9771554e382af11e83cd79f1a646cb7",
    input={
        "input": "https://replicate.delivery/mgxm/e48d7acb-260c-4c6e-a5e5-582e4b5a3274/mnist.png"
    }
)

# The vganapati/mnist-classification 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/vganapati/mnist-classification/api#output-schema
    print(item)

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

Run vganapati/mnist-classification 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": "vganapati/mnist-classification:f3d94d920835d9ae085f0f0eb2ed8ff9f9771554e382af11e83cd79f1a646cb7",
    "input": {
      "input": "https://replicate.delivery/mgxm/e48d7acb-260c-4c6e-a5e5-582e4b5a3274/mnist.png"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

3

Generated in

0 milliseconds

vganapati/mnist-classification:f3d94d920835d9ae085f0f0eb2ed8ff9f9771554e382af11e83cd79f1a646cb7

Prediction

Model

ID

gxasabtg6rdutie3tffjy3ledu

Status

Succeeded

Source

Web

Hardware

–

Total duration

1.1s

Created

over 3 years ago

Input

input

{
  "input": "https://replicate.delivery/mgxm/11a2016a-0f7c-42d3-abe6-8bcd4a90e84a/mnist.png"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run vganapati/mnist-classification using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "vganapati/mnist-classification:f3d94d920835d9ae085f0f0eb2ed8ff9f9771554e382af11e83cd79f1a646cb7",
  {
    input: {
      input: "https://replicate.delivery/mgxm/11a2016a-0f7c-42d3-abe6-8bcd4a90e84a/mnist.png"
    }
  }
);

console.log(output);

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

pip install replicate

Import the client:

import replicate

Run vganapati/mnist-classification using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "vganapati/mnist-classification:f3d94d920835d9ae085f0f0eb2ed8ff9f9771554e382af11e83cd79f1a646cb7",
    input={
        "input": "https://replicate.delivery/mgxm/11a2016a-0f7c-42d3-abe6-8bcd4a90e84a/mnist.png"
    }
)

# The vganapati/mnist-classification 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/vganapati/mnist-classification/api#output-schema
    print(item)

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

Run vganapati/mnist-classification 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": "vganapati/mnist-classification:f3d94d920835d9ae085f0f0eb2ed8ff9f9771554e382af11e83cd79f1a646cb7",
    "input": {
      "input": "https://replicate.delivery/mgxm/11a2016a-0f7c-42d3-abe6-8bcd4a90e84a/mnist.png"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

3

Generated in

0.6 seconds

vganapati/mnist-classification:f3d94d920835d9ae085f0f0eb2ed8ff9f9771554e382af11e83cd79f1a646cb7

Prediction

Model

ID

6pafc7hmvfbnjgkv3kmjjdv36e

Status

Succeeded

Source

Web

Hardware

–

Total duration

1.0s

Created

over 3 years ago

Input

input

{
  "input": "https://replicate.delivery/mgxm/4732668e-0ee5-4c45-b41b-4ad72c8506ea/mnist.png"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run vganapati/mnist-classification using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "vganapati/mnist-classification:f3d94d920835d9ae085f0f0eb2ed8ff9f9771554e382af11e83cd79f1a646cb7",
  {
    input: {
      input: "https://replicate.delivery/mgxm/4732668e-0ee5-4c45-b41b-4ad72c8506ea/mnist.png"
    }
  }
);

console.log(output);

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

pip install replicate

Import the client:

import replicate

Run vganapati/mnist-classification using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "vganapati/mnist-classification:f3d94d920835d9ae085f0f0eb2ed8ff9f9771554e382af11e83cd79f1a646cb7",
    input={
        "input": "https://replicate.delivery/mgxm/4732668e-0ee5-4c45-b41b-4ad72c8506ea/mnist.png"
    }
)

# The vganapati/mnist-classification 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/vganapati/mnist-classification/api#output-schema
    print(item)

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

Run vganapati/mnist-classification 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": "vganapati/mnist-classification:f3d94d920835d9ae085f0f0eb2ed8ff9f9771554e382af11e83cd79f1a646cb7",
    "input": {
      "input": "https://replicate.delivery/mgxm/4732668e-0ee5-4c45-b41b-4ad72c8506ea/mnist.png"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

4

Generated in

0.6 seconds