Hyeongwon/P9-split3_only_answer_Qwen3-4B-Base_0402-01-5e-6 is a 4 billion parameter language model developed by Hyeongwon, fine-tuned from Qwen3-4B-Base. This model is specifically trained using Supervised Fine-Tuning (SFT) with the TRL framework to generate direct answers. It is optimized for conversational AI where the primary goal is to provide concise and relevant responses to user queries, leveraging its 32768 token context length.
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Model Overview
Hyeongwon/P9-split3_only_answer_Qwen3-4B-Base_0402-01-5e-6 is a 4 billion parameter language model, fine-tuned from the base Hyeongwon/Qwen3-4B-Base model. This iteration has undergone Supervised Fine-Tuning (SFT) using the TRL library, specifically targeting the generation of direct answers.
Key Capabilities
- Answer Generation: Optimized to provide concise and relevant answers to questions.
- Base Model: Built upon the Qwen3-4B-Base architecture, inheriting its foundational language understanding.
- Context Length: Supports a substantial context window of 32768 tokens, allowing for processing longer prompts and maintaining conversational coherence.
Training Details
The model was trained using the SFT method within the TRL framework. The training process utilized specific versions of key libraries:
- TRL: 0.25.1
- Transformers: 4.57.3
- Pytorch: 2.6.0
- Datasets: 3.6.0
- Tokenizers: 0.22.2
This fine-tuned model is particularly suitable for applications requiring direct and focused responses, such as chatbots or question-answering systems.