Hyeongwon/P2-split2_prob_Qwen3-8B-Base_0325-01
Hyeongwon/P2-split2_prob_Qwen3-8B-Base_0325-01 is an 8 billion parameter causal language model, fine-tuned from ChuGyouk/Qwen3-8B-Base using SFT with TRL. This model is designed for text generation tasks, leveraging its base architecture and fine-tuning to produce coherent and contextually relevant outputs. It offers a 32768 token context length, making it suitable for processing longer inputs and generating extended responses.
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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.