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Google has introduced three new merchandise which might be a part of the Gemma 2 household, a sequence of open AI fashions that had been launched in June. The brand new choices embrace Gemma 2 2B, ShieldGemma, and Gemma Scope.
Gemma 2 2B is a 2 billion parameter choice, becoming a member of the prevailing 27 billion and 9 billion parameter sizes. In response to Google, this new measurement balances efficiency with effectivity, and may outperform different fashions in its class, together with all GPT-3.5 fashions.
It’s optimized with the NVIDIA TensorRT-LLM library and is out there as an NVIDIA NIM, making it very best for quite a lot of deployment varieties, equivalent to knowledge facilities, cloud, native workstations, PCs, and edge gadgets. Gemma 2 2B additionally integrates with Keras, JAX, Hugging Face, NVIDIA NeMo, Ollama, and Gemma.cpp, and can quickly combine with MediaPipe as nicely.
And due to its small measurement, it will possibly run on the free tier of T4 GPUs in Google Colab, which Google believes will make “experimentation and growth simpler than ever.”
It’s accessible now through Kaggle, Hugging Face, or Vertex AI Mannequin Backyard, and can be utilized inside Google AI Studio.
Subsequent, ShieldGemma is a sequence of security classifiers for detecting dangerous content material in mannequin inputs and outputs. It particularly targets hate speech, harassment, sexually specific content material, and harmful content material. The ShieldGemma fashions are open and designed to allow collaboration and transparency within the AI growth neighborhood, and add to the prevailing suite of security classifiers within the firm’s Accountable AI Toolkit.
It’s accessible in several mannequin sizes to satisfy totally different wants. For instance, the 2B mannequin is good for on-line classification, whereas the 9B and 27B can present higher efficiency for offline eventualities the place latency isn’t a priority. In response to Google, all mannequin sizes use NVIDIA velocity optimizations to enhance efficiency.
And at last, Gemma Scope gives higher transparency into how Gemma 2 fashions come to their selections, and may allow researchers to know how Gemma 2 identifies patterns, processes info, and makes predictions. It makes use of sparse autoencoders (SAEs) to take a look at particular factors within the mannequin and “unpack the dense, complicated info processed by Gemma 2, increasing it right into a type that’s simpler to research and perceive,” Google defined in a weblog publish.
“These releases signify our ongoing dedication to offering the AI neighborhood with the instruments and sources wanted to construct a future the place AI advantages everybody. We consider that open entry, transparency, and collaboration are important for growing secure and useful AI,” Google wrote.
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