Hyeongwon/PS_only_answer_Qwen3-4B-Base_0328-01-1e-5-seed45 is a 4 billion parameter language model developed by Hyeongwon, fine-tuned from Hyeongwon/Qwen3-4B-Base using the TRL framework. This model is specifically trained with Supervised Fine-Tuning (SFT) to generate direct answers to questions, rather than engaging in conversational turns. With a context length of 32768 tokens, its primary use case is for applications requiring concise, direct responses to user queries.
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Overview
Hyeongwon/PS_only_answer_Qwen3-4B-Base_0328-01-1e-5-seed45 is a 4 billion parameter language model, fine-tuned by Hyeongwon from the base model Hyeongwon/Qwen3-4B-Base. This model leverages the TRL (Transformer Reinforcement Learning) framework and was specifically trained using Supervised Fine-Tuning (SFT) to focus on providing direct answers to questions. It is designed to generate concise responses without engaging in extended dialogue, making it suitable for specific question-answering tasks.
Key Capabilities
- Direct Question Answering: Optimized to provide straightforward answers to user questions.
- Fine-tuned Performance: Benefits from SFT training for improved response generation in its target domain.
- TRL Framework: Developed using the TRL library, indicating a focus on advanced training techniques.
Good for
- Applications requiring immediate, non-conversational answers to queries.
- Integrating into systems where a model needs to extract and present information directly.
- Use cases where a compact 4B parameter model with a 32768 token context length is advantageous for efficiency and performance in question-answering.