Sahabat-AI/gemma2-9b-cpt-sahabatai-v1-base
The Sahabat-AI/gemma2-9b-cpt-sahabatai-v1-base is a 9 billion parameter decoder-only language model, developed by PT GoTo Gojek Tokopedia Tbk and AI Singapore, built upon the Gemma2 9B CPT SEA-Lionv3 base. It has undergone continued pre-training on approximately 50 billion tokens, specifically optimized for Indonesian language and its various dialects, including Javanese and Sundanese. This model excels in general language capabilities across these Southeast Asian languages, making it suitable for applications requiring strong performance in the Indonesian linguistic context.
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Sahabat-AI/gemma2-9b-cpt-sahabatai-v1-base Overview
This model is a 9 billion parameter decoder-only language model, co-initiated by Indonesian tech and telecommunication companies GoTo Group and Indosat Ooredoo Hutchison, and developed by PT GoTo Gojek Tokopedia Tbk and AI Singapore. It is a continued pre-trained version of the Gemma2 9B CPT SEA-Lionv3 base model, specifically enhanced for the Indonesian language and its dialects.
Key Capabilities
- Multilingual Proficiency: Optimized for Indonesian, Javanese, and Sundanese languages, in addition to English.
- Extensive Pre-training: Continued pre-training on approximately 50 billion tokens, including significant Indonesian, Javanese, and Sundanese datasets.
- General Language Tasks: Evaluated on the SEA HELM (BHASA) benchmark for tasks like Question Answering, Sentiment Analysis, Toxicity Detection, Translation, Summarization, Causal Reasoning, and Natural Language Inference.
- Strong Localized Performance: Achieves an overall score of 64.123 on the SEA HELM benchmark for Bahasa Indonesia, Javanese, and Sundanese, outperforming several other 7-9B models in this domain.
- Gemma Community License: Licensed under the Gemma Community License.
Good For
- Applications requiring robust language understanding and generation in Indonesian, Javanese, and Sundanese.
- Developers and researchers focusing on Southeast Asian language processing.
- Tasks such as content creation, customer support, and information retrieval in the Indonesian linguistic context.