nateraw / aidc-ai-business-marcoroni-13b

Cold

Public
86 runs
A100 (80GB)

Run with an API

Playground API Examples README Versions

Prediction

nateraw/aidc-ai-business-marcoroni-13b:6cf4ddac2546aa3d612ed47202489a417a86ae2e42ed5d5f80e04470e39904fd

Model

nateraw/aidc-ai-business-marcoroni-13b:6cf4ddac

alpkaojb2vsgnkl6iqxinmwzhy

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

86.5s

Created

over 1 year ago

Input

top_k: 50
top_p: 0.95
message: Write a haiku about machine learning
temperature: 0.4
max_new_tokens: 256

{
  "top_k": 50,
  "top_p": 0.95,
  "message": "Write a haiku about machine learning",
  "temperature": 0.4,
  "max_new_tokens": 256
}

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 nateraw/aidc-ai-business-marcoroni-13b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "nateraw/aidc-ai-business-marcoroni-13b:6cf4ddac2546aa3d612ed47202489a417a86ae2e42ed5d5f80e04470e39904fd",
  {
    input: {
      top_k: 50,
      top_p: 0.95,
      message: "Write a haiku about machine learning",
      temperature: 0.4,
      max_new_tokens: 256
    }
  }
);

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 nateraw/aidc-ai-business-marcoroni-13b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "nateraw/aidc-ai-business-marcoroni-13b:6cf4ddac2546aa3d612ed47202489a417a86ae2e42ed5d5f80e04470e39904fd",
    input={
        "top_k": 50,
        "top_p": 0.95,
        "message": "Write a haiku about machine learning",
        "temperature": 0.4,
        "max_new_tokens": 256
    }
)

# The nateraw/aidc-ai-business-marcoroni-13b 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/nateraw/aidc-ai-business-marcoroni-13b/api#output-schema
    print(item, end="")

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

Run nateraw/aidc-ai-business-marcoroni-13b 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": "6cf4ddac2546aa3d612ed47202489a417a86ae2e42ed5d5f80e04470e39904fd",
    "input": {
      "top_k": 50,
      "top_p": 0.95,
      "message": "Write a haiku about machine learning",
      "temperature": 0.4,
      "max_new_tokens": 256
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

In the digital realm, Machine learning sprouts like seeds, Learning, evolving, growing.

Generated in

6.4 seconds

Share Report

Prediction

nateraw/aidc-ai-business-marcoroni-13b:6cf4ddac2546aa3d612ed47202489a417a86ae2e42ed5d5f80e04470e39904fd

Model

nateraw/aidc-ai-business-marcoroni-13b:6cf4ddac

dwjkbvjb4qzkkrwyz27swcfsfq

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

3.0s

Created

over 1 year ago

Input

top_k: 50
top_p: 0.4
message: Write a short joke about machine learning
temperature: 0.9
max_new_tokens: 256

{
  "top_k": 50,
  "top_p": 0.4,
  "message": "Write a short joke about machine learning",
  "temperature": 0.9,
  "max_new_tokens": 256
}

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 nateraw/aidc-ai-business-marcoroni-13b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "nateraw/aidc-ai-business-marcoroni-13b:6cf4ddac2546aa3d612ed47202489a417a86ae2e42ed5d5f80e04470e39904fd",
  {
    input: {
      top_k: 50,
      top_p: 0.4,
      message: "Write a short joke about machine learning",
      temperature: 0.9,
      max_new_tokens: 256
    }
  }
);

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 nateraw/aidc-ai-business-marcoroni-13b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "nateraw/aidc-ai-business-marcoroni-13b:6cf4ddac2546aa3d612ed47202489a417a86ae2e42ed5d5f80e04470e39904fd",
    input={
        "top_k": 50,
        "top_p": 0.4,
        "message": "Write a short joke about machine learning",
        "temperature": 0.9,
        "max_new_tokens": 256
    }
)

# The nateraw/aidc-ai-business-marcoroni-13b 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/nateraw/aidc-ai-business-marcoroni-13b/api#output-schema
    print(item, end="")

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

Run nateraw/aidc-ai-business-marcoroni-13b 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": "6cf4ddac2546aa3d612ed47202489a417a86ae2e42ed5d5f80e04470e39904fd",
    "input": {
      "top_k": 50,
      "top_p": 0.4,
      "message": "Write a short joke about machine learning",
      "temperature": 0.9,
      "max_new_tokens": 256
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Why did the machine learning algorithm go to the gym? To increase its weights and bench press its performance.

Generated in

3.0 seconds

Share Report

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nateraw / aidc-ai-business-marcoroni-13b

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Prediction

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Output

Logs (alpkaojb2vsgnkl6iqxinmwzhy)

Logs (dwjkbvjb4qzkkrwyz27swcfsfq)