tayaee/Qwen2.5-1.5B-Korean-SFT-smoke

TEXT GENERATIONPricing:Input $0.04 / Cached $0.008 / Output $0.08Concurrent Unit Cost:1Model Size:1.5BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Aug 27, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The tayaee/Qwen2.5-1.5B-Korean-SFT-smoke model is an instruction-tuned causal language model from the Qwen2.5 series, developed by Qwen Team. With 1.54 billion parameters and a 32,768-token context length, it offers enhanced capabilities in coding, mathematics, instruction following, and long-text generation. This model is particularly optimized for understanding structured data and generating structured outputs like JSON, alongside robust multilingual support for over 29 languages, including Korean.

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Qwen2.5-1.5B-Korean-SFT-smoke Overview

This model is an instruction-tuned variant of the Qwen2.5 series, developed by the Qwen Team, featuring 1.54 billion parameters. It builds upon the Qwen2 architecture with significant improvements across several key areas, making it a versatile choice for various NLP tasks.

Key Capabilities

  • Enhanced Knowledge & Reasoning: Significantly improved capabilities in coding and mathematics, leveraging specialized expert models.
  • Instruction Following: Demonstrates substantial advancements in adhering to instructions and generating long texts (up to 8K tokens).
  • Structured Data Handling: Excels at understanding structured data, such as tables, and generating structured outputs, particularly JSON.
  • Robustness to Prompts: More resilient to diverse system prompts, which enhances role-play implementation and condition-setting for chatbots.
  • Long Context Support: Supports a full context length of 32,768 tokens and can generate up to 8,192 tokens.
  • Multilingual Support: Offers comprehensive support for over 29 languages, including Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, and Korean.

Good For

  • Applications requiring strong instruction following and structured output generation.
  • Tasks involving coding and mathematical reasoning.
  • Generating long-form content or processing extensive textual inputs.
  • Multilingual applications, especially those targeting Korean and other supported languages.
  • Chatbot implementations that benefit from resilient system prompt handling and role-play capabilities.

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