Hyeongwon/P9-split1_3times_prob_Qwen3-4B-Base_0319-02
Hyeongwon/P9-split1_3times_prob_Qwen3-4B-Base_0319-02 is a 4 billion parameter language model fine-tuned from Hyeongwon/Qwen3-4B-Base using the TRL framework. This model has a context length of 32768 tokens and was trained with Supervised Fine-Tuning (SFT). It is designed for general text generation tasks, building upon its base Qwen3 architecture.
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Model Overview
Hyeongwon/P9-split1_3times_prob_Qwen3-4B-Base_0319-02 is a 4 billion parameter language model, fine-tuned from the Hyeongwon/Qwen3-4B-Base model. This iteration was developed using the TRL framework, specifically employing Supervised Fine-Tuning (SFT) as its training procedure.
Key Capabilities
- Text Generation: Capable of generating coherent and contextually relevant text based on user prompts.
- Base Model Enhancement: Builds upon the foundational capabilities of the Qwen3-4B-Base model, likely improving performance on general language understanding and generation tasks through fine-tuning.
- Long Context Support: Inherits a substantial context length of 32768 tokens, allowing it to process and generate longer sequences of text while maintaining coherence.
Training Details
The model's training process utilized the following framework versions:
- 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 suitable for developers looking for a Qwen3-based model with specific SFT enhancements for various text generation applications.