| 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. |
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| Primary Use Cases: | | GPT-SW3 can generate coherent text in multiple languages and perform text tasks by casting them as text generation tasks. |
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| Limitations: | | Bias, Safety, Generation diversity issues, Hallucination, Overrepresentation/Underrepresentation of certain viewpoints, Stereotypes, May generate inappropriate content |
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| 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 |
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| Data Volume: | |
| Methodology: | | Trained with the NeMo Megatron GPT implementation. |
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| Model Architecture: | | Decoder-only transformer language model. |
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| Input Output |
| Input Format: | | Raw text or instruction data in chat format. |
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| Accepted Modalities: | |
| Output Format: | |
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