ChuGyouk/F_R18_T3
ChuGyouk/F_R18_T3 is an 8 billion parameter language model fine-tuned from ChuGyouk/F_R18, utilizing the TRL library for its training. This model is designed for text generation tasks, offering a 32768 token context length. Its fine-tuning process aims to enhance its conversational and generative capabilities, making it suitable for interactive applications.
Loading preview...
Model Overview
ChuGyouk/F_R18_T3 is an 8 billion parameter language model, representing a fine-tuned iteration of the ChuGyouk/F_R18 base model. It was developed using the Transformer Reinforcement Learning (TRL) library, indicating a focus on optimizing its generative performance through supervised fine-tuning (SFT).
Key Capabilities
- Text Generation: The model is primarily designed for generating coherent and contextually relevant text based on user prompts.
- Extended Context Window: It supports a substantial context length of 32768 tokens, allowing for processing and generating longer sequences of text while maintaining context.
- Fine-tuned Performance: The SFT training approach aims to improve the model's ability to follow instructions and produce high-quality outputs for conversational or creative text generation tasks.
Training Details
The model's training procedure involved Supervised Fine-Tuning (SFT) using the TRL library. This method typically involves training on a dataset of high-quality prompt-response pairs to align the model's outputs with desired behaviors. The development environment included TRL 0.24.0, Transformers 5.2.0, Pytorch 2.10.0, Datasets 4.3.0, and Tokenizers 0.22.2.