meta/codellama-7b-python | Run with an API on Replicate

Input

prompt

*string

Shift + Return to add a new line

# sum 2 numbers
def s# sum 2 numbers
def s

Prompt to send to CodeLlama.

max_new_tokens

integer

(minimum: 1)

Maximum number of tokens to generate. A word is generally 2-3 tokens

Default: 128

temperature

number

(minimum: 0.01, maximum: 5)

Adjusts randomness of outputs, greater than 1 is random and 0 is deterministic, 0.75 is a good starting value.

Default: 0.75

top_p

number

(minimum: 0, maximum: 1)

When decoding text, samples from the top p percentage of most likely tokens; lower to ignore less likely tokens

Default: 0.9

top_k

integer

(minimum: 0)

When decoding text, samples from the top k most likely tokens; lower to ignore less likely tokens

Default: 50

stop_sequences

string

Shift + Return to add a new line

A comma-separated list of sequences to stop generation at. For example, '<end>,<stop>' will stop generation at the first instance of 'end' or '<stop>'.

debug

boolean

provide debugging output in logs

Default: false

Run this model in Node.js with one line of code:

npx create-replicate --model=meta/codellama-7b-python

or set up a project from scratch

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

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,
      top_k: 250,
      top_p: 0.95,
      prompt: "# sum 2 numbers\ndef s",
      temperature: 0.95,
      max_new_tokens: 500
    }
  }
);

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=<paste-your-token-here>

Find your API token in your account settings.

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

# 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=<paste-your-token-here>

Find your API token in your account settings.

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,
      "top_k": 250,
      "top_p": 0.95,
      "prompt": "# sum 2 numbers\\ndef s",
      "temperature": 0.95,
      "max_new_tokens": 500
    }
  }' \
  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 seconds

Tweak it Iterate in playground Report View full prediction

Run time and cost

This model costs approximately $0.0058 to run on Replicate, or 172 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia L40S GPU hardware. Predictions typically complete within 6 seconds.

Readme

CodeLlama is a family of fine-tuned Llama 2 models for coding. This is CodeLlama-7b-python, a 7 billion parameter Llama model tuned for writing Python.