tanzir11/llm – Run with an API on Replicate

tanzir11 / llm

Cold

Public
102 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=tanzir11/llm

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 tanzir11/llm using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "tanzir11/llm:0115fd6c6a9b1deed47a63258c13a0ee65cc3eeb5c20a747bbd651914e602237",
  {
    input: {
      debug: false,
      top_k: 50,
      top_p: 0.9,
      temperature: 0.75,
      system_prompt: "You are a helpful assistant.",
      max_new_tokens: 128,
      min_new_tokens: -1
    }
  }
);
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 tanzir11/llm using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "tanzir11/llm:0115fd6c6a9b1deed47a63258c13a0ee65cc3eeb5c20a747bbd651914e602237",
    input={
        "debug": False,
        "top_k": 50,
        "top_p": 0.9,
        "temperature": 0.75,
        "system_prompt": "You are a helpful assistant.",
        "max_new_tokens": 128,
        "min_new_tokens": -1
    }
)

# The tanzir11/llm 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/tanzir11/llm/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 tanzir11/llm 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": "0115fd6c6a9b1deed47a63258c13a0ee65cc3eeb5c20a747bbd651914e602237",
    "input": {
      "debug": false,
      "top_k": 50,
      "top_p": 0.9,
      "temperature": 0.75,
      "system_prompt": "You are a helpful assistant.",
      "max_new_tokens": 128,
      "min_new_tokens": -1
    }
  }' \
  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 costs approximately $0.013 to run on Replicate, or 76 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 14 seconds. The predict time for this model varies significantly based on the inputs.

Readme

This model doesn't have a readme.