google-deepmind/gemma-2-2b:996e491a | Run with an API on Replicate

Version

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google-deepmind /gemma-2-2b:996e491a

Playground API

Input

prompt

string

Shift + Return to add a new line

Prompt to send to the model.

Default: "Write me a poem about Machine Learning."

max_new_tokens

integer

(minimum: 1, maximum: 4096)

Maximum number of tokens to generate. A word is generally 2-3 tokens

Default: 1024

temperature

number

(minimum: 0.1, maximum: 4)

Adjusts randomness of outputs, greater than 1 is random and 0 is deterministic, 0.75 is a good starting value.

Default: 0.6

Including top_p and 2 more...

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

npx create-replicate --model=google-deepmind/gemma-2-2b

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 google-deepmind/gemma-2-2b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "google-deepmind/gemma-2-2b:996e491a2cc5abe01bfe9371a791c8a0242172474e4ac5931671379d89961dec",
  {
    input: {
      top_k: 50,
      top_p: 0.9,
      prompt: "Write me a poem about Machine Learning.",
      temperature: 0.6,
      max_new_tokens: 1024,
      repetition_penalty: 1.2
    }
  }
);

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 google-deepmind/gemma-2-2b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "google-deepmind/gemma-2-2b:996e491a2cc5abe01bfe9371a791c8a0242172474e4ac5931671379d89961dec",
    input={
        "top_k": 50,
        "top_p": 0.9,
        "prompt": "Write me a poem about Machine Learning.",
        "temperature": 0.6,
        "max_new_tokens": 1024,
        "repetition_penalty": 1.2
    }
)

# The google-deepmind/gemma-2-2b 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/google-deepmind/gemma-2-2b/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 google-deepmind/gemma-2-2b 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": "google-deepmind/gemma-2-2b:996e491a2cc5abe01bfe9371a791c8a0242172474e4ac5931671379d89961dec",
    "input": {
      "top_k": 50,
      "top_p": 0.9,
      "prompt": "Write me a poem about Machine Learning.",
      "temperature": 0.6,
      "max_new_tokens": 1024,
      "repetition_penalty": 1.2
    }
  }' \
  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.