Gemma 2 (9B) (Deprecated)

0.315

Chat

Offline

Gemma 2 (9B) (Deprecated)

Google Gemma 2 (9B) API represents a significant step forward in the development of efficient and powerful language models.

Try it now

Creates a chat completion

const { OpenAI } = require('openai');

const api = new OpenAI({
  baseURL: 'https://api.aimlapi.com/v1',
  apiKey: '<YOUR_API_KEY>',
});

const main = async () => {
  const result = await api.chat.completions.create({
    model: 'google/gemma-2-9b-it',
    messages: [
      {
        role: 'system',
        content: 'You are an AI assistant who knows everything.',
      },
      {
        role: 'user',
        content: 'Tell me, why is the sky blue?'
      }
    ],
  });

  const message = result.choices[0].message.content;
  console.log(`Assistant: ${message}`);
};

main();

AI Playground

Test all API models in the sandbox environment before you integrate. We provide more than 200 models to integrate into your app.

Testimonials

Our Clients' Voices

Riaz Uddin

Data Governance Specialist

The AI/ML API has completely transformed how I approach AI projects. Access to over 100 models through a single API is a game-changer!

Jamie Lawson

Community Engagement Manager

The extensive model library is impressive. I’ve been able to experiment with different models effortlessly, thanks to the unified API.

Marjorie Patrick

Chief Knowledge Officer (CKO)

AI/ML API has been a game-changer for my AI projects. It's incredibly easy to integrate, offers impressive performance, and supports a wide range of ML tasks. The documentation is clear, support is responsive, and it scales seamlessly from testing to production. Highly recommended for developers looking to leverage AI effectively.

Gemma 2 (9B) (Deprecated)

Gemma 2 (9B): Efficient, open-source language model with competitive performance.

Gemma 2 (9B) Description

Model Name: Google Gemma 2 (9B)
Developer: Google
Release Date: 2024
Version: 2
Model Type: Text (Language Model)

Gemma 2 (9B) is a 9 billion parameter language model that offers competitive performance compared to larger models while maintaining a practical size. It is designed to be an open model, allowing for widespread use and adaptation by the developer community.

Key Features

Interleaved local-global attentions
Group-query attention
Trained using knowledge distillation
Competitive performance against models 2-3 times larger
Open-source availability

Technical Details

Architecture

The Gemma 2 (9B) model incorporates several technical modifications to enhance its performance:

Interleaved local-global attentions: This technique, based on the work of Beltagy et al. (2020a), allows the model to efficiently process both local and global context information.
Group-query attention: Implemented based on the research by Ainslie et al. (2023), this mechanism likely improves the model's ability to handle complex queries and relationships within the text.
Knowledge distillation: Unlike its predecessor, which used next token prediction, Gemma 2 (9B) is trained using knowledge distillation techniques. This approach, pioneered by Hinton et al. (2015), allows the model to learn from a larger, more complex model while maintaining a smaller size.

Performance Metrics

The model is described as delivering "the best performance for their size" and offering "competitive alternatives to models that are 2-3 × bigger".

Usage

Code samples

Creates a chat completion

const { OpenAI } = require('openai');

const api = new OpenAI({
  baseURL: 'https://api.aimlapi.com/v1',
  apiKey: '<YOUR_API_KEY>',
});

const main = async () => {
  const result = await api.chat.completions.create({
    model: 'google/gemma-2-9b-it',
    messages: [
      {
        role: 'system',
        content: 'You are an AI assistant who knows everything.',
      },
      {
        role: 'user',
        content: 'Tell me, why is the sky blue?'
      }
    ],
  });

  const message = result.choices[0].message.content;
  console.log(`Assistant: ${message}`);
};

main();

Ethical Considerations

While not explicitly mentioned in the provided information, it's important for developers to consider potential biases in the model's outputs and use it responsibly. As with any large language model, care should be taken to ensure that the model's responses are appropriate and do not perpetuate harmful biases or misinformation.

Licensing

Gemma is provided under and subject to the Gemma Terms of Use found at ai.google.dev/gemma/terms

Conclusion

Google Gemma 2 (9B) represents a significant step forward in the development of efficient and powerful language models. Its innovative architecture and training techniques allow it to achieve impressive performance while maintaining a relatively small size. This makes it an attractive option for developers who need high-quality language processing capabilities but may have constraints on computational resources.For software developers looking to integrate advanced language processing into their applications, Gemma 2 (9B) offers a compelling balance of performance and practicality. Its open-source nature also allows for customization and fine-tuning to specific use cases, making it a versatile tool in the natural language processing toolkit.

Try it now