We saw a lot of large language models launched this year by various companies like OpenAI, Mistral, and Meta. Now, Google joins the party! They launched its Gemma 2 series in 27 billion and 9 billion parameter sizes earlier this year. Google is back with its latest addition, Gemma 2 2B.
What makes Google’s Gemma 2 2B Special?
Google launches Gemma 2 2B, a small and flexible model, with built-in safety advancements and great performance.
“We’re excited to introduce the Gemma 2 2B model, a highly anticipated addition to the Gemma 2 family. This lightweight model produces outsized results by learning from larger models through distillation”
The key features are:
1) Greater efficiency in small size
We have seen many large language models like Meta’s LLama 3.1 with 405 billion parameters. Instead of following the trend of releasing models with a large number of parameters, Google decided to go the other way. It released a small and compact model that contains 2 billion parameters in this new series.
Despite being small in size, the model is very efficient. It can be deployed across various devices with ease and it uses very less computation resources.
2) Safety
One of the key areas of focus while launching this model has been safety. Google is encouraging the field of responsible AI.
“These releases represent our ongoing commitment to providing the AI community with the tools and resources needed to build a future where AI benefits everyone.We believe that open access, transparency, and collaboration are essential for developing safe and beneficial AI.”
3) Transparency
Google has launched GemmaScope to help researchers and developers gain access to how Gemma 2 has been built. It acts like a powerful microscope.
GemmaScope uses sparse autoencoders (SAEs) to zoom in on specific points within the model and make its inner workings more interpretable. There are also interactive demos available on Neuronpedia that will help the general public to analyze the model behaviour without writing any code.
There are also Codes and examples available on Google Colab for developers to experiment with.
4) Exceptional Performance
On the Chatbot Arena Elo Score, Gemma 2 has outperformed all the other open models like Mixtral, GPT 3.5, Llama 2 and Gemma 1.1.
This exceptional performance makes it a competitive choice for a wide range of applications, from natural language processing to complex data analysis.
5) Cost-effective and Flexibility
Gemma 2 2B is very flexible in deployment. All sizes of Gemma 2 leverage NVIDIA speed optimizations for efficient performance across hardware. The model can be deployed on various environments like data centres, cloud, local workstations, PCs, and edge devices. It offers seamless integration with various platforms like Keras, HuggingFace and many more.
6) ShieldGemma
To make sure developers and researchers deploy open models responsibly to ensure Safety, Google has launched Shield Gemma. They are a series of state-of-the-art safety classifiers designed to detect and mitigate harmful content in AI models’ inputs and outputs.
ShieldGemma has been built specifically targeting 4 key areas of harm: Hate Speech, Harassment, Sexually explicit content and Dangerous content. The below diagram may help you understand how ShieldGemma has been integrated with Gemma 2 2B to ensure safety
The open nature of ShieldGemma encourages transparency and collaboration within the AI community, contributing to the future of ML industry safety standards.
Conclusion
Based on people’s opinions, it is safe to say that Gemma 2 2B is a game-changer in the field of AI. Google puts a strong emphasis on safety and transparency by releasing ShieldGemma and GemmaScope. It is interesting to see how other companies react to this news.
