technillogue/llama-89 – Run with an API on Replicate

technillogue / llama-89

Cold

Public
0 runs
CPU

Iterate in playground

Run with an API

Playground API Examples README Versions

Input

prompt

*string

Shift + Return to add a new line

Prompt to send to the model.

system_prompt

string

Shift + Return to add a new line

System prompt to send to the model. This is prepended to the prompt and helps guide system behavior.

Default: ""

max_tokens

integer

(minimum: 1)

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

Default: 512

min_tokens

integer

(minimum: -1)

Minimum number of tokens to generate. To disable, set to -1. A word is generally 2-3 tokens.

temperature

number

(minimum: 0, maximum: 5)

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

Default: 0.7

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: 0.95

top_k

integer

(minimum: -1)

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

Default: 0

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>'.

length_penalty

number

(minimum: 0, maximum: 5)

A parameter that controls how long the outputs are. If < 1, the model will tend to generate shorter outputs, and > 1 will tend to generate longer outputs.

Default: 1

presence_penalty

number

A parameter that penalizes repeated tokens regardless of the number of appearances. As the value increases, the model will be less likely to repeat tokens in the output.

Default: 0

seed

integer

Random seed. Leave blank to randomize the seed.

prompt_template

string

Shift + Return to add a new line

Template for formatting the prompt. Can be an arbitrary string, but must contain the substring `{prompt}`.

Default: "{prompt}"

log_performance_metrics

boolean

Default: false

max_new_tokens

integer

(minimum: 1)

This parameter has been renamed to max_tokens. max_new_tokens only exists for backwards compatibility purposes. We recommend you use max_tokens instead. Both may not be specified.

min_new_tokens

integer

(minimum: -1)

This parameter has been renamed to min_tokens. min_new_tokens only exists for backwards compatibility purposes. We recommend you use min_tokens instead. Both may not be specified.

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

npx create-replicate --model=technillogue/llama-89

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 technillogue/llama-89 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "technillogue/llama-89:1b8a0ce6eb03080cc97a8c0ef5939e9e9a0ea7e871f70212b15bf085d3233965",
  {
    input: {
      top_k: 0,
      top_p: 0.95,
      max_tokens: 512,
      temperature: 0.7,
      system_prompt: "",
      length_penalty: 1,
      prompt_template: "{prompt}",
      presence_penalty: 0,
      log_performance_metrics: false
    }
  }
);

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 technillogue/llama-89 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "technillogue/llama-89:1b8a0ce6eb03080cc97a8c0ef5939e9e9a0ea7e871f70212b15bf085d3233965",
    input={
        "top_k": 0,
        "top_p": 0.95,
        "max_tokens": 512,
        "temperature": 0.7,
        "system_prompt": "",
        "length_penalty": 1,
        "prompt_template": "{prompt}",
        "presence_penalty": 0,
        "log_performance_metrics": False
    }
)

# The technillogue/llama-89 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/technillogue/llama-89/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 technillogue/llama-89 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": "technillogue/llama-89:1b8a0ce6eb03080cc97a8c0ef5939e9e9a0ea7e871f70212b15bf085d3233965",
    "input": {
      "top_k": 0,
      "top_p": 0.95,
      "max_tokens": 512,
      "temperature": 0.7,
      "system_prompt": "",
      "length_penalty": 1,
      "prompt_template": "{prompt}",
      "presence_penalty": 0,
      "log_performance_metrics": false
    }
  }' \
  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.

Run time and cost

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

Readme

This model doesn't have a readme.