Hyeongwon/P2-split2_bs512_epoch5_5e-5_prob_Qwen3-4B-Base_0320-01
The Hyeongwon/P2-split2_bs512_epoch5_5e-5_prob_Qwen3-4B-Base_0320-01 model is a 4 billion parameter language model fine-tuned from Hyeongwon/Qwen3-4B-Base using TRL. This model has been trained with Supervised Fine-Tuning (SFT) to enhance its conversational capabilities. It is designed for text generation tasks, particularly for responding to open-ended questions and engaging in dialogue.
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Model Overview
Hyeongwon/P2-split2_bs512_epoch5_5e-5_prob_Qwen3-4B-Base_0320-01 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 the TRL (Transformer Reinforcement Learning) library.
Key Capabilities
- Text Generation: Excels at generating coherent and contextually relevant text based on user prompts.
- Conversational AI: Fine-tuned with Supervised Fine-Tuning (SFT) to improve its ability to handle conversational inputs and generate appropriate responses.
- Question Answering: Demonstrated capability in answering open-ended questions, as shown in the quick start example.
Training Details
The model underwent a Supervised Fine-Tuning (SFT) process. The training utilized specific framework versions:
- TRL: 0.25.1
- Transformers: 4.57.3
- Pytorch: 2.6.0
- Datasets: 3.6.0
- Tokenizers: 0.22.2
Use Cases
This model is suitable for applications requiring:
- Generating creative or informative text.
- Developing chatbots or conversational agents.
- Assisting with content creation by providing detailed responses to prompts.