Model Overview

Hyeongwon/PS_prob_seed44_Qwen3-4B-Base_0322-01 is a 4 billion parameter language model, fine-tuned from the Hyeongwon/Qwen3-4B-Base architecture. This model was developed by Hyeongwon and trained using Supervised Fine-Tuning (SFT) with the TRL library.

Key Characteristics

• Base Model: Fine-tuned from Hyeongwon/Qwen3-4B-Base.
• Training Method: Utilizes Supervised Fine-Tuning (SFT).
• Frameworks: Trained with TRL (version 0.25.1), Transformers (version 4.57.3), PyTorch (version 2.6.0), Datasets (version 3.6.0), and Tokenizers (version 0.22.2).
• Context Length: Supports a context length of 32768 tokens.

Use Cases

This model is suitable for various text generation tasks where a fine-tuned 4 billion parameter model is appropriate. Developers can integrate it using the Hugging Face pipeline for quick text generation, as demonstrated in the provided quick start example. Its training with SFT suggests a focus on generating coherent and contextually relevant text based on the fine-tuning data.