| Model Type | | Text-to-text, Decoder-only large language models |
|
| Use Cases |
| Areas: | | Content Creation, Research, Education |
|
| Applications: | | Text Generation, Chatbots, Text Summarization |
|
| Limitations: | | Training data limitations, Context and task complexity, Language ambiguity, Factual accuracy issues |
|
| Considerations: | | Guidelines provided for responsible use. |
|
|
| Supported Languages | |
| Training Details |
| Data Sources: | | Web Documents, Code, Mathematics |
|
| Data Volume: | |
| Hardware Used: | |
|
| Safety Evaluation |
| Methodologies: | | Structured evaluations, Internal red-teaming |
|
| Findings: | | Acceptable thresholds for internal policies |
|
| Risk Categories: | | Child safety, Content safety, Representational harms, Memorization, Large-scale harms |
|
| Ethical Considerations: | |
|
| Responsible Ai Considerations |
| Fairness: | | Scrutiny and data pre-processing done to mitigate biases. |
|
| Transparency: | | Model card provides details on architecture, capabilities, and processes. |
|
| Accountability: | | Google as the developer has oversight on model deployments. |
|
| Mitigation Strategies: | | Developers are encouraged to follow guidelines for responsible use. |
|
|
| Input Output |
| Input Format: | | Text string (e.g., prompt or question) |
|
| Output Format: | | Generated English-language text |
|
|