| Model Type | | language model, text generation | 
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| Use Cases | 
| Areas: |  |  | Applications: | | Pre-release for research and evaluation of the capabilities of Large Language Models for the Nordic languages. | 
 |  | Primary Use Cases: | | GPT-SW3 can generate coherent text in multiple languages and perform text tasks by casting them as text generation tasks. | 
 |  | Limitations: | | Bias, Safety, Generation diversity issues, Hallucination, Overrepresentation/Underrepresentation of certain viewpoints, Stereotypes, May generate inappropriate content | 
 |  | 
| Supported Languages | | da (Unknown), sv (Unknown), no (Unknown), en (Unknown), is (Unknown) | 
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| Training Details | 
| Data Sources: | | laion/OIG, databricks/databricks-dolly-15k, OpenAssistant/oasst1 | 
 |  | Data Volume: |  |  | Methodology: | | Trained with the NeMo Megatron GPT implementation. | 
 |  | Model Architecture: | | Decoder-only transformer language model. | 
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| Input Output | 
| Input Format: | | Raw text or instruction data in chat format. | 
 |  | Accepted Modalities: |  |  | Output Format: |  |  |