ChuGyouk/F_R15_T2 is an 8 billion parameter language model, fine-tuned from the ChuGyouk/F_R15 base model using Supervised Fine-Tuning (SFT) with TRL. This model is designed for general text generation tasks, leveraging its 32768 token context length for coherent and extended outputs. It is optimized for conversational AI and question-answering, building upon its predecessor's capabilities.
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Model Overview
ChuGyouk/F_R15_T2 is an 8 billion parameter language model developed by ChuGyouk. It is a fine-tuned iteration of the ChuGyouk/F_R15 base model, specifically enhanced through Supervised Fine-Tuning (SFT) using the TRL (Transformer Reinforcement Learning) library. This fine-tuning process aims to improve the model's ability to generate coherent and contextually relevant text.
Key Capabilities
- Text Generation: Excels at generating human-like text based on given prompts, suitable for various creative and conversational applications.
- Context Handling: Benefits from a substantial 32768 token context window, allowing it to process and generate longer, more detailed responses while maintaining context.
- Instruction Following: As an SFT-tuned model, it is designed to follow instructions more effectively, making it suitable for interactive applications.
Training Details
The model was trained using the TRL framework, specifically employing Supervised Fine-Tuning (SFT). The training procedure utilized TRL version 0.24.0, Transformers 5.2.0, Pytorch 2.10.0, Datasets 4.3.0, and Tokenizers 0.22.2. Further details on the training run can be visualized via Weights & Biases.
Good For
- Conversational AI: Its fine-tuned nature makes it well-suited for chatbots and interactive dialogue systems.
- Creative Writing: Can be used for generating stories, scripts, or other forms of creative content.
- Question Answering: Capable of providing detailed answers to complex questions, leveraging its extended context window.