Hyeongwon/P9-split4_only_answer_Qwen3-4B-Base_0402-01-5e-6 is a 4 billion parameter language model, fine-tuned from Hyeongwon/Qwen3-4B-Base using SFT with TRL. This model is specifically optimized for generating direct answers, making it suitable for question-answering tasks where concise, focused responses are desired. It processes inputs with a context length of 32768 tokens, providing ample capacity for detailed prompts.
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Model Overview
This model, Hyeongwon/P9-split4_only_answer_Qwen3-4B-Base_0402-01-5e-6, is a 4 billion parameter language model derived from Hyeongwon/Qwen3-4B-Base. It has been fine-tuned using Supervised Fine-Tuning (SFT) with the TRL library, focusing on generating direct and concise answers to user queries.
Key Capabilities
- Direct Answer Generation: Optimized to provide focused responses, making it suitable for specific question-answering scenarios.
- Base Model Enhancement: Builds upon the capabilities of the Qwen3-4B-Base architecture.
- Context Handling: Supports a substantial context length of 32768 tokens, allowing for processing of longer prompts and detailed questions.
Training Details
The model was trained using the TRL (Transformer Reinforcement Learning) framework, specifically employing SFT. The training environment utilized TRL 0.25.1, Transformers 4.57.3, Pytorch 2.6.0, Datasets 3.6.0, and Tokenizers 0.22.2.
Good For
- Applications requiring concise and direct answers.
- Integrating into systems where the model's output needs to be a focused response rather than a conversational dialogue.
- Developers looking for a fine-tuned Qwen3-4B-Base variant with a specific answer-only generation objective.