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Average Ratings 0 Ratings
Description
The Gemma family consists of advanced, lightweight models developed using the same innovative research and technology as the Gemini models. These cutting-edge models are equipped with robust security features that promote responsible and trustworthy AI applications, achieved through carefully curated data sets and thorough refinements. Notably, Gemma models excel in their various sizes—2B, 7B, 9B, and 27B—often exceeding the performance of some larger open models. With the introduction of Keras 3.0, users can experience effortless integration with JAX, TensorFlow, and PyTorch, providing flexibility in framework selection based on specific tasks. Designed for peak performance and remarkable efficiency, Gemma 2 is specifically optimized for rapid inference across a range of hardware platforms. Furthermore, the Gemma family includes diverse models that cater to distinct use cases, ensuring they adapt effectively to user requirements. These lightweight language models feature a decoder and have been trained on an extensive array of textual data, programming code, and mathematical concepts, which enhances their versatility and utility in various applications.
Description
MedGemma is an innovative suite of Gemma 3 variants specifically designed to excel in the analysis of medical texts and images. This resource empowers developers to expedite the creation of AI applications focused on healthcare. Currently, MedGemma offers two distinct variants: a multimodal version with 4 billion parameters and a text-only version featuring 27 billion parameters. The 4B version employs a SigLIP image encoder, which has been meticulously pre-trained on a wealth of anonymized medical data, such as chest X-rays, dermatological images, ophthalmological images, and histopathological slides. Complementing this, its language model component is trained on a wide array of medical datasets, including radiological images and various pathology visuals. MedGemma 4B can be accessed in both pre-trained versions, denoted by the suffix -pt, and instruction-tuned versions, marked by the suffix -it. For most applications, the instruction-tuned variant serves as the optimal foundation to build upon, making it particularly valuable for developers. Overall, MedGemma represents a significant advancement in the integration of AI within the medical field.
API Access
Has API
API Access
Has API
Integrations
Hugging Face
Vertex AI
C
C#
C++
Gemma
Gemma 3
Google AI Studio
Google Cloud Platform
Google Colab
Integrations
Hugging Face
Vertex AI
C
C#
C++
Gemma
Gemma 3
Google AI Studio
Google Cloud Platform
Google Colab
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Country
United States
Website
ai.google.dev/gemma
Vendor Details
Company Name
Google DeepMind
Founded
2010
Country
United Kingdom
Website
deepmind.google/models/gemma/medgemma/