aisingapore/Llama-SEA-LION-v3-8B-IT

TEXT GENERATIONPricing:Input $0.2 / Cached $0.028 / Output $0.32Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Dec 11, 2024License:llama3.1Architecture:Transformer0.0K Featherless Exclusive Cold

Llama-SEA-LION-v3-8B-IT is an instruction-tuned decoder-only large language model developed by AI Singapore, based on the Llama 3.1 architecture. It is specifically designed and optimized for Southeast Asian languages, supporting Burmese, Chinese, English, Filipino, Indonesian, Javanese, Khmer, Lao, Malay, Sundanese, Tamil, Thai, and Vietnamese. With a context length of 128k tokens, this model excels in general language understanding and instruction-following tasks across the SEA region.

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Llama-SEA-LION-v3-8B-IT: Southeast Asian Language Model

Llama-SEA-LION-v3-8B-IT is an instruction-tuned large language model developed by AI Singapore, part of the SEA-LION (Southeast Asian Languages In One Network) collection. Built upon the Llama 3.1 architecture, this decoder-only model has undergone continued pre-training and instruction tuning specifically for the Southeast Asian region. It supports a broad range of languages including Burmese, Chinese, English, Filipino, Indonesian, Javanese, Khmer, Lao, Malay, Sundanese, Tamil, Thai, and Vietnamese, utilizing the default Llama 3.1 8B Instruct tokenizer.

Key Capabilities and Features

  • Multilingual Support: Optimized for 13 Southeast Asian languages, enhancing performance in regional contexts.
  • Extended Context Length: Features a substantial 128k token context window, suitable for processing longer inputs and conversations.
  • Instruction Following: Evaluated on SEA-IFEval and SEA-MTBench, demonstrating proficiency in adhering to prompt constraints and engaging in multi-turn conversations.
  • General Language Understanding: Performance assessed using the SEA-HELM benchmark across tasks like Question Answering, Sentiment Analysis, Translation, and Summarization.

Use Cases and Considerations

This model is ideal for applications requiring strong language understanding and generation capabilities in Southeast Asian languages. It is particularly suited for tasks such as chatbots, content generation, and language translation within the SEA region. Users should be aware that the model has not been aligned for safety and may exhibit limitations common to LLMs, such as hallucination and occasional inconsistencies in reasoning. Developers are advised to implement their own safety fine-tuning and validation measures.

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