Model Overview

Hyeongwon/P2-split2_prob_Qwen3-8B-Base_0325-01 is an 8 billion parameter language model, fine-tuned from the ChuGyouk/Qwen3-8B-Base architecture. This model was developed using Supervised Fine-Tuning (SFT) with the TRL library, indicating a focus on improving performance for specific tasks through direct instruction.

Key Capabilities

• Text Generation: Optimized for generating human-like text based on given prompts.
• Context Handling: Features a substantial 32768 token context length, allowing it to process and generate longer, more complex narratives or responses while maintaining coherence.

Training Details

The model underwent a training procedure utilizing SFT, a common method for adapting pre-trained language models to specific downstream tasks. The training leveraged several key frameworks:

• 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 applications requiring robust text generation capabilities, especially where understanding and maintaining context over longer sequences is crucial.