Hugging Face Overview
Gemma 3 (12B) Overview
This model is a 12 billion parameter variant of the Gemma 3 family, developed by Google DeepMind. It is a multimodal model capable of processing both text and image inputs to generate text outputs. Key features include a substantial 128K token context window and support for over 140 languages, making it versatile for global applications.
Key Capabilities
- Multimodal Processing: Accepts text and images (normalized to 896x896 resolution) as input.
- Extensive Context: Utilizes a 128K token context window for comprehensive understanding.
- Multilingual Support: Trained on data in over 140 languages.
- Diverse Task Performance: Excels in text generation, image understanding, question answering, summarization, and reasoning.
- Efficient Deployment: Designed for deployment in environments with limited resources, such as laptops or cloud infrastructure.
Benchmark Highlights (Gemma 3 PT 12B)
- Reasoning: Achieves 84.2 on HellaSwag (10-shot) and 72.6 on BIG-Bench Hard (few-shot).
- STEM & Code: Scores 74.5 on MMLU (5-shot) and 71.0 on GSM8K (8-shot).
- Multilingual: Reaches 64.3 on MGSM and 69.4 on Global-MMLU-Lite.
- Multimodal: Attains 82.3 on DocVQA (val) and 71.2 on VQAv2.
Good For
- Content Creation: Generating creative text formats, marketing copy, and email drafts.
- Conversational AI: Powering chatbots and virtual assistants.
- Research & Education: Serving as a foundation for VLM/NLP research and language learning tools.
- Image Analysis: Extracting and interpreting visual data for text communications.