Model Overview
ChuGyouk/F_R6_T3 is an 8 billion parameter language model, representing a fine-tuned iteration of the ChuGyouk/F_R6 base model. This version has undergone supervised fine-tuning (SFT) using the TRL library, enhancing its ability to follow instructions and generate coherent text based on prompts. It supports a substantial context length of 32,768 tokens, allowing for processing and generating longer sequences of text.
Key Capabilities
- Instruction Following: Optimized through SFT to better understand and respond to user instructions.
- Text Generation: Capable of generating diverse and contextually relevant text, as demonstrated by its quick start example for open-ended questions.
- Extended Context: Benefits from a 32,768 token context window, suitable for tasks requiring extensive input or generating lengthy outputs.
Training Details
The model was trained using the TRL (Transformer Reinforcement Learning) framework, specifically employing SFT. The training environment utilized TRL version 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 adapt the base F_R6 model for more interactive and instruction-driven applications.
Good For
- Conversational AI: Its instruction-tuned nature makes it suitable for chatbots and interactive agents.
- Question Answering: Can be used to generate detailed responses to complex questions.
- General Text Generation: Applicable for various creative and analytical text generation tasks where a large context window is beneficial.