ChuGyouk/R18_1
ChuGyouk/R18_1 is an 8 billion parameter language model, fine-tuned from ChuGyouk/Qwen3-8B-Base with a 32768 token context length. This model was trained using Supervised Fine-Tuning (SFT) with the TRL framework. It is designed for general text generation tasks, building upon the Qwen3 architecture.
Loading preview...
Overview
ChuGyouk/R18_1 is an 8 billion parameter language model, fine-tuned from the ChuGyouk/Qwen3-8B-Base architecture. It leverages a substantial 32768 token context length, making it suitable for processing longer inputs and generating coherent, extended responses. The model was developed using the TRL (Transformer Reinforcement Learning) framework, specifically through Supervised Fine-Tuning (SFT).
Key Capabilities
- Text Generation: Excels at generating human-like text based on given prompts.
- Instruction Following: Capable of following instructions for various text-based tasks, as demonstrated by its fine-tuning process.
- Long Context Understanding: Benefits from its 32768 token context window, allowing for better comprehension and generation in scenarios requiring extensive contextual awareness.
Training Details
The model was trained using Supervised Fine-Tuning (SFT) with the TRL library. The development environment included specific versions of key frameworks:
- TRL: 0.24.0
- Transformers: 5.2.0
- Pytorch: 2.10.0
- Datasets: 4.3.0
- Tokenizers: 0.22.2
Use Cases
This model is well-suited for applications requiring robust text generation, such as chatbots, content creation, and general conversational AI, particularly where understanding and generating text within a broad context is important.