ChuGyouk/F_R18
ChuGyouk/F_R18 is an 8 billion parameter language model, fine-tuned from ChuGyouk/Qwen3-8B-Base using TRL. This model is designed for general text generation tasks, leveraging its 32768 token context length for processing longer inputs. Its training methodology focuses on supervised fine-tuning, making it suitable for conversational AI and question-answering applications.
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Overview
ChuGyouk/F_R18 is an 8 billion parameter language model, built upon the ChuGyouk/Qwen3-8B-Base architecture. It has been specifically fine-tuned using the TRL (Transformer Reinforcement Learning) library, indicating a focus on optimizing its response generation capabilities through supervised fine-tuning (SFT). The model supports a substantial context length of 32768 tokens, allowing it to handle extensive conversational histories or detailed prompts.
Key Capabilities
- General Text Generation: Capable of generating coherent and contextually relevant text based on user prompts.
- Long Context Understanding: Benefits from a 32768 token context window, enabling it to process and respond to longer inputs and maintain conversational flow over extended interactions.
- Instruction Following: Fine-tuned with SFT, suggesting improved ability to follow instructions and generate targeted responses.
Training Details
The model's training involved supervised fine-tuning (SFT) using the TRL framework. The specific versions of the frameworks used were TRL 0.24.0, Transformers 5.2.0, Pytorch 2.10.0, Datasets 4.3.0, and Tokenizers 0.22.2. This fine-tuning process aims to enhance the model's performance on various language understanding and generation tasks.