Prediction

Model

meta/codellama-7b-python:27009070

dz6tualbnqbcfd66cxb3bwec7a

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

57.3s

Created

over 2 years ago by replicate-internal

Webhook

–

Input

prompt: # sum 2 numbers def s
max_new_tokens: 500
temperature: 0.95
top_p: 0.95
top_k: 250
debug: false

{
  "debug": false,
  "max_new_tokens": 500,
  "prompt": "# sum 2 numbers\ndef s",
  "temperature": 0.95,
  "top_k": 250,
  "top_p": 0.95
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_EZM**********************************

This is your API token. Keep it to yourself.

Import and set up the client:

import Replicate from "replicate";

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

Run meta/codellama-7b-python using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "meta/codellama-7b-python:27009070dd7c1166317c35cd637f3cb9170e43d38234110089ea355a85a67deb",
  {
    input: {
      debug: false,
      max_new_tokens: 500,
      prompt: "# sum 2 numbers\ndef s",
      temperature: 0.95,
      top_k: 250,
      top_p: 0.95
    }
  }
);

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

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_EZM**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

Run meta/codellama-7b-python using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "meta/codellama-7b-python:27009070dd7c1166317c35cd637f3cb9170e43d38234110089ea355a85a67deb",
    input={
        "debug": False,
        "max_new_tokens": 500,
        "prompt": "# sum 2 numbers\ndef s",
        "temperature": 0.95,
        "top_k": 250,
        "top_p": 0.95
    }
)

# The meta/codellama-7b-python 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/meta/codellama-7b-python/api#output-schema
    print(item, end="")

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

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_EZM**********************************

This is your API token. Keep it to yourself.

Run meta/codellama-7b-python 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": "meta/codellama-7b-python:27009070dd7c1166317c35cd637f3cb9170e43d38234110089ea355a85a67deb",
    "input": {
      "debug": false,
      "max_new_tokens": 500,
      "prompt": "# sum 2 numbers\\ndef s",
      "temperature": 0.95,
      "top_k": 250,
      "top_p": 0.95
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

1():
    return 2 + 4
def s2(x, y):
    return x + y
def s3(x, y):
    return x + y
a = s1()

Generated in

1.1 second

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