IzzuddinAzzam/llama3-indonesian-sft
IzzuddinAzzam/llama3-indonesian-sft is an 8 billion parameter Llama 3 instruction-tuned model developed by IzzuddinAzzam, specifically fine-tuned for Indonesian language tasks. This model leverages Unsloth for accelerated training and is optimized for performance in Indonesian natural language processing applications. It is designed to provide robust language understanding and generation capabilities within an 8192 token context window for Indonesian content.
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Overview
IzzuddinAzzam/llama3-indonesian-sft is an 8 billion parameter Llama 3 model, specifically fine-tuned for the Indonesian language. Developed by IzzuddinAzzam, this model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster training compared to standard methods. It builds upon the unsloth/llama-3-8b-Instruct-bnb-4bit base model, adapting its instruction-following capabilities to Indonesian linguistic nuances.
Key Capabilities
- Indonesian Language Proficiency: Optimized for understanding and generating text in Indonesian.
- Instruction Following: Inherits and adapts the instruction-following capabilities of the Llama 3 base model.
- Efficient Training: Benefits from Unsloth's accelerated training techniques, making it a resource-efficient option for Indonesian NLP.
Good For
- Applications requiring a performant Indonesian-specific large language model.
- Developers looking for a Llama 3 variant with strong Indonesian language support.
- Tasks such as text generation, summarization, and question-answering in Indonesian.