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TAME LLM is an open-source initiative focused on building and releasing large language models optimized for Traditional Mandarin and the linguistic context of Taiwan. The project includes models such as Llama-3-Taiwan-70B, which are fine-tuned versions of large transformer architectures trained on extensive corpora containing both Traditional Mandarin and English text. These models are designed to support applications such as conversational AI, knowledge retrieval, and domain-specific reasoning in fields like manufacturing, law, healthcare, and electronics. The training pipeline leverages high-performance computing infrastructure and frameworks such as NVIDIA NeMo and Megatron to enable large-scale model training. Taiwan-LLM aims to improve language understanding and generation for Traditional Mandarin users by incorporating region-specific datasets and evaluation benchmarks.
Features
- Large language models fine-tuned for Traditional Mandarin and English usage
- Training pipelines built on NVIDIA NeMo and large-scale GPU infrastructure
- Support for conversational AI, reasoning, and retrieval-augmented generation
- Domain-specific datasets covering industries such as legal, medical, and manufacturing
- Fine-tuning workflows using frameworks such as Axolotl and distributed training tools
- High-context language model variants supporting extended token contexts
Project Samples
