Hyeongwon/P9-split1_only_answer_Qwen3-4B-Base_0402-01-5e-6 is a 4 billion parameter language model, fine-tuned from Hyeongwon/Qwen3-4B-Base using the TRL framework. This model was trained with Supervised Fine-Tuning (SFT) and is designed for text generation tasks, particularly for answering questions. Its architecture is based on the Qwen3-4B-Base model, offering a context length of 32768 tokens, making it suitable for applications requiring concise, direct responses.
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Overview
Hyeongwon/P9-split1_only_answer_Qwen3-4B-Base_0402-01-5e-6 is a 4 billion parameter language model, fine-tuned from the Hyeongwon/Qwen3-4B-Base architecture. This model leverages the TRL (Transformer Reinforcement Learning) framework for its training, specifically utilizing Supervised Fine-Tuning (SFT).
Key Capabilities
- Question Answering: Optimized for generating direct and concise answers to user queries.
- Text Generation: Capable of producing coherent text based on provided prompts.
- Base Model Enhancement: Builds upon the robust Qwen3-4B-Base, inheriting its foundational language understanding.
Good For
- Applications requiring straightforward answers to questions.
- Integration into systems where a compact yet capable language model is needed for text generation.
- Developers looking for a fine-tuned Qwen3-4B variant with a focus on direct response generation.