justmalhar / meta-llama-3.2-1b

Meta Llama 3.2 1B

Cold

Public
185 runs
L40S

Iterate in playground

Run with an API

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Prediction

justmalhar/meta-llama-3.2-1b:c4a7531b0c6f3701bd470744223fef3d26c8dd11e6f05733650bb329555543a7

Model

justmalhar/meta-llama-3.2-1b:c4a7531b

v5x8tw40t5rgp0cj5kp80jfke4

Status

Succeeded

Source

Web

Hardware

A40

Total duration

44.9s

Created

9 months ago

Input

top_p: 0.95
prompt: How many r's are there in the word strawberry?
max_tokens: 512
temperature: 0.6

{
  "top_p": 0.95,
  "prompt": "How many r's are there in the word strawberry?",
  "max_tokens": 512,
  "temperature": 0.6
}

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-3.2-1b 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-3.2-1b:c4a7531b0c6f3701bd470744223fef3d26c8dd11e6f05733650bb329555543a7",
  {
    input: {
      top_p: 0.95,
      prompt: "How many r's are there in the word strawberry?",
      max_tokens: 512,
      temperature: 0.6
    }
  }
);

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-3.2-1b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "justmalhar/meta-llama-3.2-1b:c4a7531b0c6f3701bd470744223fef3d26c8dd11e6f05733650bb329555543a7",
    input={
        "top_p": 0.95,
        "prompt": "How many r's are there in the word strawberry?",
        "max_tokens": 512,
        "temperature": 0.6
    }
)

# The justmalhar/meta-llama-3.2-1b 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-3.2-1b/api#output-schema
    print(item, end="")

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

Run justmalhar/meta-llama-3.2-1b 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-3.2-1b:c4a7531b0c6f3701bd470744223fef3d26c8dd11e6f05733650bb329555543a7",
    "input": {
      "top_p": 0.95,
      "prompt": "How many r\'s are there in the word strawberry?",
      "max_tokens": 512,
      "temperature": 0.6
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

There are three R's in the word "strawberry".

Generated in

0.5 seconds

Tweak it Share Report

Prediction

justmalhar/meta-llama-3.2-1b:c4a7531b0c6f3701bd470744223fef3d26c8dd11e6f05733650bb329555543a7

Model

justmalhar/meta-llama-3.2-1b:c4a7531b

np03vjx1ynrgp0cj5kptwjtjwr

Status

Succeeded

Source

Web

Hardware

A40

Total duration

0.3s

Created

9 months ago

Input

top_p: 0.95
prompt: How many r's are there in the word raspberry?
max_tokens: 512
temperature: 0.6

{
  "top_p": 0.95,
  "prompt": "How many r's are there in the word raspberry?",
  "max_tokens": 512,
  "temperature": 0.6
}

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-3.2-1b 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-3.2-1b:c4a7531b0c6f3701bd470744223fef3d26c8dd11e6f05733650bb329555543a7",
  {
    input: {
      top_p: 0.95,
      prompt: "How many r's are there in the word raspberry?",
      max_tokens: 512,
      temperature: 0.6
    }
  }
);

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-3.2-1b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "justmalhar/meta-llama-3.2-1b:c4a7531b0c6f3701bd470744223fef3d26c8dd11e6f05733650bb329555543a7",
    input={
        "top_p": 0.95,
        "prompt": "How many r's are there in the word raspberry?",
        "max_tokens": 512,
        "temperature": 0.6
    }
)

# The justmalhar/meta-llama-3.2-1b 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-3.2-1b/api#output-schema
    print(item, end="")

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

Run justmalhar/meta-llama-3.2-1b 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-3.2-1b:c4a7531b0c6f3701bd470744223fef3d26c8dd11e6f05733650bb329555543a7",
    "input": {
      "top_p": 0.95,
      "prompt": "How many r\'s are there in the word raspberry?",
      "max_tokens": 512,
      "temperature": 0.6
    }
  }' \
  https://api.replicate.com/v1/predictions

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