ChuGyouk/F_R19
ChuGyouk/F_R19 is an 8 billion parameter causal language model, fine-tuned from ChuGyouk/Qwen3-8B-Base. This model is optimized for general text generation tasks, leveraging its base architecture and SFT training for improved conversational and creative text outputs. With a 32768 token context length, it is suitable for applications requiring extended conversational memory or processing longer documents.
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Model Overview
ChuGyouk/F_R19 is an 8 billion parameter language model, fine-tuned from the ChuGyouk/Qwen3-8B-Base architecture. This model has undergone Supervised Fine-Tuning (SFT) using the TRL framework, aiming to enhance its capabilities in generating coherent and contextually relevant text.
Key Capabilities
- General Text Generation: Excels at producing human-like text based on given prompts.
- Extended Context Handling: Supports a substantial context window of 32768 tokens, allowing for more detailed and longer interactions or document processing.
- Instruction Following: Benefits from its fine-tuning process to better understand and respond to user instructions.
Training Details
The model was trained using the TRL (Transformer Reinforcement Learning) library, specifically employing Supervised Fine-Tuning (SFT). The training environment utilized Transformers version 5.2.0, PyTorch 2.10.0, and Datasets 4.3.0, ensuring a robust and modern training pipeline. Further details on the training run can be found on Weights & Biases.