jinhomok/Sample_Model
jinhomok/Sample_Model is a 2.5 billion parameter instruction-tuned causal language model developed by jinhomok, based on the Google Gemma-2B architecture. This model is primarily focused on Korean language tasks, having been fine-tuned on the jinhomok/sample_data2026 dataset. It features an 8192-token context length and is optimized for text generation in Korean, making it suitable for applications requiring Korean language understanding and generation.
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Model Overview
jinhomok/Sample_Model is a 2.5 billion parameter, instruction-tuned language model built upon the google/gemma-2b base architecture. Developed by jinhomok, this model is specifically designed for text generation tasks, with a particular emphasis on the Korean language. It leverages a substantial 8192-token context window, allowing for processing and generating longer sequences of text.
Key Capabilities
- Korean Language Proficiency: Fine-tuned on the
jinhomok/sample_data2026dataset, indicating a strong focus on Korean language understanding and generation. - Text Generation: Optimized for various text generation tasks, benefiting from its instruction-tuned nature.
- Extended Context: Supports an 8192-token context length, enabling more coherent and contextually relevant outputs for longer inputs.
- Gemma-2B Foundation: Inherits the robust capabilities of the Google Gemma-2B model, providing a solid base for its specialized applications.
Good For
- Applications requiring Korean text generation.
- Tasks involving Korean language understanding where a compact yet capable model is needed.
- Developers looking for a Gemma-based model with specific Korean language fine-tuning.