Model Type | text-generation, multi-turn dialogue, language understanding |
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Use Cases |
Areas: | Traditional Mandarin NLP tasks, English NLP tasks |
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Applications: | Multi-turn dialogue, RAG (Retrieval-Augmented Generation), Language understanding, Entity recognition, Function calling |
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Primary Use Cases: | NLP tasks, Legal, Manufacturing, Medical, Electronics |
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Additional Notes | The compute and data for training were generously sponsored by local organizations. |
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Supported Languages | Traditional Mandarin (High), English (High) |
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Training Details |
Data Sources: | High-quality Traditional Mandarin, English corpus, Legal, Manufacturing, Medical, Electronics domains |
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Methodology: | Finetuned using NVIDIA NeMo Framework |
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Input Output |
Accepted Modalities: | |
Performance Tips: | Set system message for optimal results. |
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Release Notes |
Version: | |
Notes: | Initial release of Llama-3-Taiwan-70B-Instruct-rc1 for public testing. |
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