nateraw/codellama-13b-instruct:4d4dfb56 – Run with an API on Replicate

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nateraw /codellama-13b-instruct:4d4dfb56

Playground API

Input

message

*string

Shift + Return to add a new line

system_prompt

string

Shift + Return to add a new line

The system prompt to use (for chat/instruct models only)

Default: "Provide answers in Python"

max_new_tokens

integer

The maximum number of tokens the model should generate as output.

Default: 256

temperature

number

The value used to modulate the next token probabilities.

Default: 0.2

top_p

number

A probability threshold for generating the output. If < 1.0, only keep the top tokens with cumulative probability >= top_p (nucleus filtering). Nucleus filtering is described in Holtzman et al. (http://arxiv.org/abs/1904.09751).

Default: 0.9

top_k

integer

The number of highest probability tokens to consider for generating the output. If > 0, only keep the top k tokens with highest probability (top-k filtering).

Default: 50

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

npx create-replicate --model=nateraw/codellama-13b-instruct

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-13b-instruct using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "nateraw/codellama-13b-instruct:4d4dfb567b910309c9501d56807864fc069ffcd2867552aea073c4b374eef309",
  {
    input: {
      top_k: 50,
      top_p: 0.9,
      temperature: 0.2,
      system_prompt: "Provide answers in Python",
      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-13b-instruct using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "nateraw/codellama-13b-instruct:4d4dfb567b910309c9501d56807864fc069ffcd2867552aea073c4b374eef309",
    input={
        "top_k": 50,
        "top_p": 0.9,
        "temperature": 0.2,
        "system_prompt": "Provide answers in Python",
        "max_new_tokens": 256
    }
)

# The nateraw/codellama-13b-instruct 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-13b-instruct/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-13b-instruct 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": "4d4dfb567b910309c9501d56807864fc069ffcd2867552aea073c4b374eef309",
    "input": {
      "top_k": 50,
      "top_p": 0.9,
      "temperature": 0.2,
      "system_prompt": "Provide answers in Python",
      "max_new_tokens": 256
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

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