Hyeongwon/P9-split2_only_answer_Qwen3-4B-Base_0402-01-5e-6 is a 4 billion parameter language model fine-tuned from Hyeongwon/Qwen3-4B-Base. This model was trained using Supervised Fine-Tuning (SFT) with the TRL framework. It is designed for text generation tasks, particularly for providing direct answers to questions. The model supports a context length of 32768 tokens.
Loading preview...
Model Overview
This model, Hyeongwon/P9-split2_only_answer_Qwen3-4B-Base_0402-01-5e-6, is a 4 billion parameter language model derived from the Hyeongwon/Qwen3-4B-Base architecture. It has been specifically fine-tuned using the TRL library through a Supervised Fine-Tuning (SFT) process.
Key Capabilities
- Text Generation: Optimized for generating coherent and relevant text based on given prompts.
- Question Answering: Designed to provide direct answers, as indicated by its name "only_answer".
- Base Model: Built upon the Qwen3-4B-Base, inheriting its foundational language understanding.
Training Details
The model's training involved SFT, leveraging the TRL framework (version 0.25.1) alongside Transformers (4.57.3), PyTorch (2.6.0), Datasets (3.6.0), and Tokenizers (0.22.2). The training process can be visualized via Weights & Biases.
Use Cases
This model is suitable for applications requiring concise and direct responses to user queries, making it ideal for chatbots, conversational AI, or automated content generation where the output should primarily be an answer rather than an extended dialogue.