Google Gemma
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About
Google’s Gemma is a lightweight, state-of-the-art open language model (LLM) based on the same research used in the creation of Google’s Gemini models. Gemma family equips models with two sizes, the 2B and 7B parameters versions, where each has a base (pre-trained) and instruction-tuned modifications. It supports multi-framework tools and cross-device compatibility and is optimized for Google Cloud and NVIDIA GPUs. Developers can access Gemma models via Kaggle, Google Cloud, and Hugging Face’s Inference Endpoints, among others. The Gemma models have myriad applications, including text generation, summarization, and retrieval-augmented generation (RAG).
Platform
Task
Features
• cross-device compatibility
• text generation
• summarization
• optimized for google cloud and nvidia gpus
• lightweight
• retrieval-augmented generation (rag)
• open language model
• multi-framework tools support
FAQs
How can developers access Gemma models?
Developers can access Gemma models via Kaggle, Google Cloud, and Hugging Face’s Inference Endpoints, among others.
In which devices can Gemma models run?
Gemma models can run on various devices, including laptops, desktops, IoT, mobile, and cloud.
What are the applications of Gemma models?
The Gemma models have myriad applications, including text generation, summarization, and retrieval-augmented generation (RAG).
What tuning techniques can be used on Gemma models?
Fine-tuning techniques such as LoRA tuning and distributed training can be applied to Gemma models.
Pricing Plans
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