| Model Type | | Multilingual, Autoregressive, Language model |
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| Use Cases |
| Areas: | | Research, Commercial applications |
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| Applications: | | Reasoning, Summarization, Question answering, Tool use automation |
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| Primary Use Cases: | | Reasoning tasks, Summarization tasks, Question answering |
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| Limitations: | | May not perform well with unrecognized input structures, Deviations from prompt templates may reduce performance |
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| Considerations: | | Recommended to adhere to prompt structures for optimal performance. |
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| Additional Notes | | Command R+ optimized for multilingual and complex task automation through multiple tool use. |
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| Supported Languages | | English (Advanced), French (Advanced), Spanish (Advanced), Italian (Advanced), German (Advanced), Brazilian Portuguese (Advanced), Japanese (Advanced), Korean (Advanced), Simplified Chinese (Advanced), Arabic (Advanced), Russian (Pre-training included), Polish (Pre-training included), Turkish (Pre-training included), Vietnamese (Pre-training included), Dutch (Pre-training included), Czech (Pre-training included), Indonesian (Pre-training included), Ukrainian (Pre-training included), Romanian (Pre-training included), Greek (Pre-training included), Hindi (Pre-training included), Hebrew (Pre-training included), Persian (Pre-training included) |
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| Training Details |
| Data Sources: | | Open internet sourced datasets |
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| Methodology: | | Mixture of supervised fine-tuning and preference training for alignment with human preferences. |
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| Context Length: | |
| Model Architecture: | | Optimized transformer architecture |
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| Responsible Ai Considerations |
| Mitigation Strategies: | | Includes monitoring of harmful outputs and optimization for safe responses through preference fine-tuning. |
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| Input Output |
| Input Format: | |
| Accepted Modalities: | |
| Output Format: | |
| Performance Tips: | | Use specified prompt templates to maintain performance levels. |
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