Hugging Face Hyeongwon/P2-split5_prob_Qwen3-4B-Base_0312-01 is a 4 billion parameter language model, fine-tuned from Hyeongwon/Qwen3-4B-Base using Supervised Fine-Tuning (SFT) with the TRL framework. This model is designed for general text generation tasks, building upon the foundational capabilities of the Qwen3-4B-Base architecture. It offers a 32768 token context length, making it suitable for applications requiring processing of moderately long inputs and generating coherent responses.
Model Overview
Hyeongwon/P2-split5_prob_Qwen3-4B-Base_0312-01 is a 4 billion parameter language model developed by Hyeongwon. It is a fine-tuned variant of the Hyeongwon/Qwen3-4B-Base model, specifically 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) for specialized performance.
- Frameworks: Trained with TRL 0.25.1, Transformers 4.57.3, Pytorch 2.6.0, Datasets 3.6.0, and Tokenizers 0.22.2.
- Context Length: Supports a context window of 32768 tokens.
Intended Use Cases
This model is suitable for various text generation tasks where a 4 billion parameter model with a substantial context window is beneficial. Its SFT training suggests an optimization for following instructions and generating relevant, coherent text based on provided prompts.