nateraw/codellama-34b-python – Run with an API on Replicate

nateraw / codellama-34b-python

Cold

Public
3 runs
L40S

Run with an API

Playground API Examples README Versions

Input

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

npx create-replicate --model=nateraw/codellama-34b-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 nateraw/codellama-34b-python using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "nateraw/codellama-34b-python:9609587feed5d2cee2e2298c0eafec00c2d413f40cf82d2efeda3a259f3e4c14",
  {
    input: {
      top_k: 50,
      top_p: 0.9,
      temperature: 0.2,
      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

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 nateraw/codellama-34b-python using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "nateraw/codellama-34b-python:9609587feed5d2cee2e2298c0eafec00c2d413f40cf82d2efeda3a259f3e4c14",
    input={
        "top_k": 50,
        "top_p": 0.9,
        "temperature": 0.2,
        "max_new_tokens": 256
    }
)

# The nateraw/codellama-34b-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/nateraw/codellama-34b-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 nateraw/codellama-34b-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": "9609587feed5d2cee2e2298c0eafec00c2d413f40cf82d2efeda3a259f3e4c14",
    "input": {
      "top_k": 50,
      "top_p": 0.9,
      "temperature": 0.2,
      "max_new_tokens": 256
    }
  }' \
  https://api.replicate.com/v1/predictions

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

You can run this model locally using Cog. First, install Cog:

brew install cog

If you don’t have Homebrew, there are other installation options available.

Run this to download the model and run it in your local environment:

cog predict r8.im/nateraw/codellama-34b-python@sha256:9609587feed5d2cee2e2298c0eafec00c2d413f40cf82d2efeda3a259f3e4c14 \
  -i 'top_k=50' \
  -i 'top_p=0.9' \
  -i 'temperature=0.2' \
  -i 'max_new_tokens=256'

To learn more, take a look at the Cog documentation.

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 --gpus=all r8.im/nateraw/codellama-34b-python@sha256:9609587feed5d2cee2e2298c0eafec00c2d413f40cf82d2efeda3a259f3e4c14
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "top_k": 50,
      "top_p": 0.9,
      "temperature": 0.2,
      "max_new_tokens": 256
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

No output yet! Press "Submit" to start a prediction.

Run time and cost

This model runs on Nvidia L40S GPU hardware. We don't yet have enough runs of this model to provide performance information.

Readme

This model doesn't have a readme.