Learn Prompting🟢 Gemma
What is Gemma?
Gemma is a series of models released by Google, with some specializing in specific fields and others capable of functioning as full, foundational models.
One important aspect of the Gemma series is that all of the included models are open-source, which Google did to allow for accessibility and innovation on the same technology used for their proprietary Gemini models.
Gemma Models
Gemma 2
Gemma 2, particularly the 27B parameter version, is a strong foundational model when compared to how cheap it is, at a mere $0.3 per 1M tokens. Though its performance on reasoning benchmarks is slightly lower than most other models, its low price and accessibility as an open source model more than make up for it.
DataGemma
DataGemma is a revolutionary model integrated with Google's Data Commons, a vast repository of over 240 billion trustworthy data points from sources like the United Nations and Census Bureaus. Through this integration, the model is able to give all of its responses directly from reliable data, a great leap forwards in the fight to curb hallucination in AI models.
RecurrentGemma
RecurrentGemma is an experimental model built on a combination of a recurrent neural network with local sliding window attention. These changes presented an interesting new perspective on model architectures; RecurrentGemma-9B achieved comparable benchmark performance to Gemma-7B, despite being trained on three times less tokens.
PaliGemma
PaliGemma is a vision-language model (VLM), meaning its specifically suited for tasks that involve images and text, like generating captions for video. It opens up a whole new realm of AI use-cases, particularly for fine-tuned downstream tasks, where it performs best.
CodeGemma
CodeGemma, as the name suggests, specializes in code completion and generation. Its speed and efficiency make it a very robust model for these kinds of tasks.
Advantages of Gemma Models
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Open source: All Gemma models are open source and available on Hugging Face and Kaggle, encouraging innovation and enabling a wide range of applications without the high cost typically associated with proprietary models. This makes advanced AI accessible to researchers, developers, and businesses alike.
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Cheap: The Gemma models are highly cost-effective, especially Gemma 2, which provides strong foundational capabilities at just $0.3 per 1M tokens, making them an attractive option for developers prioritizing budget without sacrificing reasonable performance.
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Specialized: The series includes specialized models tailored for specific tasks, such as:
- DataGemma for data-driven reliability and reducing hallucinations.
- CodeGemma for efficient code generation and completion.
- PaliGemma for vision-language integration, expanding AI's capabilities in multimodal tasks.
Conclusion
The Gemma series of models released by Google is a highly innovative and versatile collection of open-source AI tools that cater to a wide range of applications. By balancing cost efficiency, specialization, and groundbreaking architectural advancements, the Gemma series empowers developers, researchers, and organizations to access cutting-edge AI technology without the barriers of high costs or proprietary restrictions.
Andres Caceres
Andres Caceres, a documentation writer at Learn Prompting, has a passion for AI, math, and education. Outside of work, he enjoys playing soccer and tennis, spending time with his three huskies, and tutoring. His enthusiasm for learning and sharing knowledge drives his dedication to making complex concepts more accessible through clear and concise documentation.