Prediction

justmalhar/meta-llama-3.2-3b:5c11ba722650525b0ab1a877d1fde44c5dab7445072e9e8e1a6a47ec2026a4d4

Model

justmalhar/meta-llama-3.2-3b:5c11ba72

ehpww4twx9rgm0cj5m2v5we5j0

Status

Succeeded

Source

Web

Hardware

A40

Total duration

1.1s

Created

7 months ago

Input

top_p: 0.95
prompt: how many s in mississippi. think step by step
max_tokens: 512
temperature: 0.7

{
  "top_p": 0.95,
  "prompt": "how many s in mississippi. think step by step",
  "max_tokens": 512,
  "temperature": 0.7
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run justmalhar/meta-llama-3.2-3b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "justmalhar/meta-llama-3.2-3b:5c11ba722650525b0ab1a877d1fde44c5dab7445072e9e8e1a6a47ec2026a4d4",
  {
    input: {
      top_p: 0.95,
      prompt: "how many s in mississippi. think step by step",
      max_tokens: 512,
      temperature: 0.7
    }
  }
);

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

Import the client:

import replicate

Run justmalhar/meta-llama-3.2-3b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "justmalhar/meta-llama-3.2-3b:5c11ba722650525b0ab1a877d1fde44c5dab7445072e9e8e1a6a47ec2026a4d4",
    input={
        "top_p": 0.95,
        "prompt": "how many s in mississippi. think step by step",
        "max_tokens": 512,
        "temperature": 0.7
    }
)

# The justmalhar/meta-llama-3.2-3b 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/justmalhar/meta-llama-3.2-3b/api#output-schema
    print(item, end="")

To learn more, take a look at the guide on getting started with Python.

Run justmalhar/meta-llama-3.2-3b 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": "justmalhar/meta-llama-3.2-3b:5c11ba722650525b0ab1a877d1fde44c5dab7445072e9e8e1a6a47ec2026a4d4",
    "input": {
      "top_p": 0.95,
      "prompt": "how many s in mississippi. think step by step",
      "max_tokens": 512,
      "temperature": 0.7
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

To determine the number of S's in "Mississippi", let's break it down: 1. We have two words: "Miss" and "Mississippi". 2. Each word starts with an "M", then has one "I", followed by "S". 3. In the first word, "Miss", there is only 1 "S". 4. In the second word, "Mississippi", there are three S's. 5. Now, let's add up the total number of S's: 1 (from "Miss") + 3 (from "Mississippi") = 4 So, the correct answer is: There are 4 S's in "Mississippi".

{
  "completed_at": "2024-09-26T06:29:40.298360Z",
  "created_at": "2024-09-26T06:29:39.178000Z",
  "data_removed": false,
  "error": null,
  "id": "ehpww4twx9rgm0cj5m2v5we5j0",
  "input": {
    "top_p": 0.95,
    "prompt": "how many s in mississippi. think step by step",
    "max_tokens": 512,
    "temperature": 0.7
  },
  "logs": "Total runtime: 0.9436671733856201",
  "metrics": {
    "predict_time": 1.02369226,
    "total_time": 1.12036
  },
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  ],
  "started_at": "2024-09-26T06:29:39.274668Z",
  "status": "succeeded",
  "urls": {
    "stream": "https://stream-g.svc.us.c.replicate.net/v1/streams/7ldp4xckspzkgx6hygpykesa4bxy7a7rkzkn27av7pzhwmdy27vq",
    "get": "https://api.replicate.com/v1/predictions/ehpww4twx9rgm0cj5m2v5we5j0",
    "cancel": "https://api.replicate.com/v1/predictions/ehpww4twx9rgm0cj5m2v5we5j0/cancel"
  },
  "version": "5c11ba722650525b0ab1a877d1fde44c5dab7445072e9e8e1a6a47ec2026a4d4"
}

Generated in

1.0 second

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