sookjung/army_model_gemma2b
TEXT GENERATIONConcurrency Cost:1Model Size:2.5BQuant:BF16Ctx Length:8kPublished:Apr 15, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
The sookjung/army_model_gemma2b is a 2.5 billion parameter causal language model developed by sookjung, based on the Google Gemma-2-2b architecture. This model is fine-tuned specifically for Korean language tasks, leveraging the sookjung/fintech_sample dataset. It is designed for text generation applications, offering a context length of 8192 tokens.
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Model Overview
The sookjung/army_model_gemma2b is a specialized language model developed by sookjung, building upon the google/gemma-2-2b base architecture. With 2.5 billion parameters and an 8192-token context window, this model is primarily focused on text generation tasks.
Key Characteristics
- Base Model: Derived from Google's Gemma-2-2b, indicating a robust and efficient foundation.
- Language Focus: Specifically fine-tuned for the Korean language, making it suitable for applications requiring strong Korean linguistic capabilities.
- Training Data: Utilizes the
sookjung/fintech_sampledataset, suggesting potential specialization or enhanced performance in fintech-related or similar domains within Korean. - Pipeline Tag: Configured for
text-generation, indicating its primary intended use for generating coherent and contextually relevant text.
Intended Use Cases
This model is particularly well-suited for:
- Generating Korean text in various applications.
- Tasks requiring understanding and generation within specific domains if the
fintech_sampledataset implies such specialization. - Applications where a compact yet capable Korean-centric language model is beneficial.