We are proud to launch SEA-LION v3.5, our first set of hybrid reasoning models trained on Southeast Asian data. Mode selection is managed through the tokenizer’s chat template and offers versatile functionality, handling both complex reasoning tasks and general text generation. Trained off our SEA-LION v3, SEA-LION v3.5 is explicitly enhanced for reasoning tasks with…
In collaboration with the HELM team at Stanford CRFM (with special thanks to Yifan Mai), we would like to announce the official release of SEA-HELM (Southeast Asian Holistic Evaluation of Language Models), a general-purpose holistic benchmark to evaluate the performance of LLMs in the Southeast Asian context. Distinctive Features Cutting-edge Components Counts for Selected Tasks…
Explore how to design fair, transparent, and representative multilingual evaluations for large language models. Large language models (LLMs) can now generate complete and coherent sentences in many more languages than most humans. Emergent abilities, such as reasoning, creative writing, and human-agent interactions, have propelled enterprises to adapt these models to suit a wide range of…