Prediction

Model

lucataco/ollama-llama3.3-70b:29f7aa41

mcsw3bc1f9rmc0ckta8t8x6f3m

Status

Succeeded

Source

Web

Hardware

L40S

Total duration

85.7s

Created

about 1 year ago

Webhook

–

Input

prompt: Who are you?
temperature: 0.7
top_p: 0.95
max_tokens: 512

{
  "max_tokens": 512,
  "prompt": "Who are you?",
  "temperature": 0.7,
  "top_p": 0.95
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_Rgg**********************************

This is your API token. Keep it to yourself.

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run lucataco/ollama-llama3.3-70b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/ollama-llama3.3-70b:29f7aa41293e897979d3e118ec8527542e5457417ae5d70e92b5f3f10033c5c3",
  {
    input: {
      max_tokens: 512,
      prompt: "Who are you?",
      temperature: 0.7,
      top_p: 0.95
    }
  }
);

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=r8_Rgg**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

Run lucataco/ollama-llama3.3-70b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/ollama-llama3.3-70b:29f7aa41293e897979d3e118ec8527542e5457417ae5d70e92b5f3f10033c5c3",
    input={
        "max_tokens": 512,
        "prompt": "Who are you?",
        "temperature": 0.7,
        "top_p": 0.95
    }
)

# The lucataco/ollama-llama3.3-70b 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/lucataco/ollama-llama3.3-70b/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=r8_Rgg**********************************

This is your API token. Keep it to yourself.

Run lucataco/ollama-llama3.3-70b 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": "lucataco/ollama-llama3.3-70b:29f7aa41293e897979d3e118ec8527542e5457417ae5d70e92b5f3f10033c5c3",
    "input": {
      "max_tokens": 512,
      "prompt": "Who are you?",
      "temperature": 0.7,
      "top_p": 0.95
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

I'm an artificial intelligence model known as Llama. Llama stands for "Large Language Model Meta AI."

Generated in

2.1 seconds

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