### Key Technical Specifications

* Model Architecture
  * Built upon Google's Gemma 2 architecture, this model is a decoder-only transformer with 9 billion parameters. It incorporates advanced techniques from the Gemini research and has been instruction-tuned for conversational applications. The model uses a specialized chat template with role-based formatting and specific delimiters for optimal performance in dialogue scenarios.

* Performance Metrics
  * The model demonstrates strong performance across various benchmarks, particularly excelling in reasoning and knowledge tasks:
    * MMLU (Massive Multitask Language Understanding): 71.3% accuracy
    * HellaSwag (commonsense reasoning): 81.9% accuracy
    * HumanEval (code generation): 40.2% pass@1
    * GSM8K (mathematical reasoning): 68.6% accuracy
    * TriviaQA (knowledge retrieval): 76.6% accuracy

### Key Technical Specifications

### 

### Model Use Cases

* Content Creation and Communication
  * Ideal for generating high-quality text content across various formats:
    * Creative text generation (poems, scripts, marketing copy)
    * Conversational AI and chatbot applications
    * Text summarization of documents and reports
* Research and Education
  * Perfect for academic and research applications:
    * Natural Language Processing research foundation
    * Interactive language learning tools
    * Knowledge exploration and question answering

### 

### Model Best Practices

* Use proper chat template: Apply the model's specific chat template with <start_of_turn> and <end_of_turn> delimiters for optimal conversational performance
* Provide clear instructions: Frame tasks with clear prompts and instructions for better results
* Consider context length: Optimize your prompts within the 8K context window for best performance
* Leverage instruction tuning: Take advantage of the model's conversational training for dialogue-based applications

### Get Started with Gemma 2 9B IT
Experience the capabilities of `gemma2-9b-it` with Groq speed:

---

## Llama Guard 4 12b: Page (mdx)