Model Overview

Hyeongwon/P2-split2_prob_Qwen3-8B-Base_0325-02-lr1e-5 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) techniques, implemented with the TRL (Transformer Reinforcement Learning) library.

Key Capabilities

• Text Generation: Optimized for generating coherent and contextually relevant text based on provided prompts.
• Base Model Enhancement: Builds upon the capabilities of the Qwen3-8B-Base model, adapting it through SFT for specific applications.
• Context Handling: Features a substantial context window of 32768 tokens, allowing it to process and generate longer sequences of text.

Training Details

The model underwent a Supervised Fine-Tuning (SFT) process. The training utilized specific versions of key frameworks:

• TRL: 0.25.1
• Transformers: 4.57.3
• Pytorch: 2.6.0
• Datasets: 3.6.0
• Tokenizers: 0.22.2

This fine-tuning approach aims to specialize the base model for improved performance in its intended use cases.