All articles tagged with #gemma
Google unveils Gemma 4 12B, a 12B open AI model that runs offline on a 16GB RAM laptop, using an encoder-free multimodal design to handle vision and audio directly, delivering strong reasoning near Google's 26B MoE model—enabling private, local AI on everyday devices.
Google releases AI Edge Gallery for Mac, letting users run Gemma 4 12B and other Gemma models locally offline with on‑device dictation via AI Edge Eloquent; the setup requires about 16GB of VRAM/unified memory, making most modern Macs eligible (except the MacBook Neo). Gemma is an open, portable family distinct from Google’s private Gemini models, and the app offers offline speed and privacy with a direct download from Google.
Google has brought its AI Edge Gallery to macOS, giving Mac users access to five Google-owned models led by Gemma 4 12B, a 12‑billion‑parameter multimodal model designed to run locally on laptops with 16GB RAM. The gallery also includes Gemma-4-E2B-it, Gemma-4-E4B-it, Gemma-3n-E2B-it, and Gemma-3n-E4B-it, all accessible offline and designed for private on-device use. In tandem, Google released the Google AI Edge Eloquent dictation app for Mac, which transcribes speech on-device, refines text, supports writing styles, and lets users add custom vocabulary for better accuracy.
Google has removed its open Gemma AI model from AI Studio following a complaint from Senator Marsha Blackburn, who claimed the model generated false accusations against her. The move appears to be a response to concerns about AI hallucinations and potential misuse, with Google emphasizing ongoing efforts to reduce such errors while restricting non-developer access to prevent inflammatory outputs.
Google removed its AI model Gemma from a developer platform after US Senator Marsha Blackburn accused it of fabricating criminal allegations against her, highlighting concerns over bias and misinformation in AI tools. Google acknowledged hallucinations as a known issue and clarified that Gemma is intended for developers and researchers, not general consumer use.
Google has introduced Gemma, a new family of AI language models that are free and open-weights, allowing them to run locally on desktop or laptop computers. These models, developed by Google DeepMind and other Google AI teams, outperform Meta's Llama 2 on several benchmarks. Gemma comes in two sizes, 2B and 7B parameters, and is available through platforms like Kaggle and Hugging Face. This release is seen as a move to compete with Meta's open-weights models and is accompanied by a "Responsible Generative AI Toolkit" aimed at promoting safe and responsible AI applications.
Google has unveiled Gemma, an open large language model designed for use on laptops and in resource-constrained environments, available in 2B and 7B parameter versions. It is released under an open license with restrictions to prevent malicious use, and comes with a Responsible Generative AI Toolkit for safety. Gemma's efficiency and extensive vocabulary make it versatile for various tasks, and it has been optimized for safety and responsible use, with training data filtered and reinforcement learning used for responsible behavior.
Google has launched Gemma, a new family of lightweight open-weight models, including Gemma 2B and Gemma 7B, inspired by its Gemini models. These dense decoder-only models are available for commercial and research usage, with access to ready-to-use Colab and Kaggle notebooks, as well as integrations with Hugging Face, MaxText, and Nvidia’s NeMo. While not open-source, developers can use the models for inferencing and fine-tune them at will. Google also released a responsible generative AI toolkit and a debugging tool to provide guidance and essential tools for creating safer AI applications with Gemma.
Google has introduced Gemma, a lightweight open AI model available in two sizes, Gemma 2B and Gemma 7B, which are designed to run directly on a developer's laptop or desktop. The models, created using the same technology as Google's Gemini AI models, come with pre-trained and instruction-tuned variants and are aimed at helping developers build AI responsibly. Google also released the Responsible Generative AI Toolkit alongside Gemma, containing a debugging tool and best practices guide for AI development. The company plans to introduce more Gemma variants in the future and has made the models accessible through platforms like Kaggle, Colab notebooks, and Google Cloud.
Google has released Gemma 2B and 7B, open-source AI models that are smaller and more accessible than its flagship Gemini model, allowing developers to use the research more freely. Despite their smaller size, Google claims Gemma models surpass larger models on key benchmarks and can run directly on a developer's computer. Gemma will be available via platforms like Kaggle, Hugging Face, and Google's Vertex AI, and comes with responsible AI toolkits to address potential risks. While it's not clear how much demand there is for smaller models like Gemma, other AI companies have also released lighter-weight versions of their flagship models.
Google has announced Gemma, an open-source AI model based on its closed-source Gemini models, aimed at assisting developers and researchers in building AI responsibly. Gemma comes in two model weights, pre-trained with text-to-text support, and surpasses larger models on key benchmarks while adhering to rigorous standards for safe and responsible outputs. It is pre-trained to filter out personal and sensitive information, tested for alignment and potential harms, and is accompanied by a Responsible Generative AI Toolkit. Gemma is available for free access on various platforms and comes with $300 in credits for first-time Google Cloud users.
Google DeepMind has introduced Gemma, its new 2B and 7B open source models, along with a Responsible Generative AI toolkit and toolchains for inference and supervised fine-tuning across major frameworks. The models are integrated with various platforms and can run on different devices. Google also offers APIs and open models for workflow, aiming to provide a wide set of capabilities for the community. Gemma's safety and responsible design are emphasized, with extensive evaluations and filtering of sensitive data. Google DeepMind will release benchmarks evaluating Gemma against other models, emphasizing transparency and community involvement in the project.