Gemma 2B It is an open-source language model by google. Features: 2b LLM, VRAM: 5.1GB, Context: 8K, License: gemma, Quantized, LLM Explorer Score: 0.35, ELO: 1004, Arc: 43.9, HellaSwag: 62.7, MMLU: 37.7, GSM8K: 5.4.
Gemma 2B It Benchmarks
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Gemma 2B It Parameters and Internals
Model Type text generation, decoder-only
Use Cases
Areas: Content creation, Research and education
Applications: Text generation, Chatbots, Text summarization
Primary Use Cases: Creative text formats, NLP research, Language learning tools
Limitations: Bias from training data, Complex task handling limitations
Considerations: Use with caution for sensitive or biased scenarios.
Additional Notes Open models from Google, built from Gemini technology.
Supported Languages English (High proficiency)
Training Details
Data Sources: Web Documents, Code, Mathematics
Data Volume:
Methodology: Decoder-only model trained with TPUs, using JAX and ML Pathways
Hardware Used:
Model Architecture: Lightweight, state-of-the-art open model
Safety Evaluation
Methodologies: Red-teaming, Human evaluation, Automated evaluation
Findings: Within acceptable thresholds
Risk Categories: CSAM, Sensitive Data Filtering, Large-scale harm
Ethical Considerations: Evaluation included representational harms, content safety, and memorization risks.
Responsible Ai Considerations
Fairness: Model includes multiple stages of filtering for potentially harmful content.
Transparency: Model architecture, training, and evaluation details are publicized.
Accountability: Google is accountable for the content and safety evaluations.
Mitigation Strategies: Mechanisms were instituted for content safety and bias reduction.
Input Output
Input Format:
Accepted Modalities:
Output Format: Generated English-language text
Performance Tips:
Release Notes
Version:
Date:
Notes: Larger variant of the model.
Version:
Date:
Notes: Instruction-tuned variant.
Rank the Gemma 2B It capabilities
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Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation
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