tvytlx/llama7b | Run with an API on Replicate

Input

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

npx create-replicate --model=tvytlx/llama7b

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 tvytlx/llama7b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "tvytlx/llama7b:9ae95232e15ead3036e49a21105d2c3a68fe6f9508db63c0bcbdf418b80fc45f",
  {
    input: {
      prompt: "why earth exists?",
      max_length: 300,
      temperature: 0.7,
      min_new_tokens: 10,
      repetition_penalty: 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 tvytlx/llama7b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "tvytlx/llama7b:9ae95232e15ead3036e49a21105d2c3a68fe6f9508db63c0bcbdf418b80fc45f",
    input={
        "prompt": "why earth exists?",
        "max_length": 300,
        "temperature": 0.7,
        "min_new_tokens": 10,
        "repetition_penalty": 1
    }
)

print(output)

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 tvytlx/llama7b 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": "tvytlx/llama7b:9ae95232e15ead3036e49a21105d2c3a68fe6f9508db63c0bcbdf418b80fc45f",
    "input": {
      "prompt": "why earth exists?",
      "max_length": 300,
      "temperature": 0.7,
      "min_new_tokens": 10,
      "repetition_penalty": 1
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

As an AI language model, I don't have a personal belief or opinion on the existence of Earth. However, scientifically speaking, Earth exists because it is one of the planets in our solar system that has the right conditions for life to exist. It has the right temperature, atmosphere, and resources to support life as we know it.

Generated in

8.8 seconds

Tweak it Iterate in playground Report View full prediction

This output was created using a different version of the model, tvytlx/llama7b:698c714e.

Run time and cost

This model costs approximately $0.017 to run on Replicate, or 58 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 A100 (80GB) GPU hardware. Predictions typically complete within 13 seconds. The predict time for this model varies significantly based on the inputs.

Readme

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Model description

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Intended use

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Ethical considerations

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Caveats and recommendations

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