Hyeongwon/P2-split2_prob_Qwen3-4B-Base_0312-01-epoch2_75 is a 4 billion parameter language model developed by Hyeongwon, fine-tuned from the Qwen3-4B-Base architecture. This model was trained using Supervised Fine-Tuning (SFT) with the TRL framework. It is designed for general text generation tasks, building upon its base model's capabilities.
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Model Overview
Hyeongwon/P2-split2_prob_Qwen3-4B-Base_0312-01-epoch2_75 is a 4 billion parameter language model developed by Hyeongwon. It is a fine-tuned variant of the Qwen3-4B-Base model, specifically trained using the TRL (Transformer Reinforcement Learning) framework.
Key Characteristics
- Base Model: Fine-tuned from Hyeongwon/Qwen3-4B-Base.
- Training Method: Utilizes Supervised Fine-Tuning (SFT).
- Framework: Developed using the TRL library, version 0.25.1.
- Context Length: Supports a context length of 32768 tokens.
Intended Use
This model is suitable for various text generation tasks, leveraging its fine-tuned capabilities. Developers can quickly integrate it using the Hugging Face transformers pipeline for tasks such as answering open-ended questions or generating creative text based on prompts.