ChuGyouk/F_R8
ChuGyouk/F_R8 is an 8 billion parameter instruction-tuned causal language model developed by ChuGyouk, fine-tuned from ChuGyouk/Llama-3.1-8B. Trained using TRL, this model is designed for general text generation tasks, particularly excelling in conversational question-answering scenarios. It processes inputs up to an 8192 token context length, making it suitable for various natural language understanding and generation applications.
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Model Overview
ChuGyouk/F_R8 is an 8 billion parameter language model, fine-tuned by ChuGyouk from the ChuGyouk/Llama-3.1-8B base model. This model leverages the TRL (Transformer Reinforcement Learning) library for its training procedure, specifically utilizing Supervised Fine-Tuning (SFT).
Key Capabilities
- Instruction Following: Designed to respond to user prompts and instructions effectively.
- Text Generation: Capable of generating coherent and contextually relevant text based on input.
- Conversational AI: Optimized for engaging in question-answering and dialogue-based interactions.
- Context Handling: Supports a context window of up to 8192 tokens, allowing for processing longer inputs and maintaining conversational history.
Training Details
The model was trained using the SFT method within the TRL framework. The training process can be visualized via Weights & Biases, indicating a structured approach to fine-tuning. Key framework versions used include TRL 0.24.0, Transformers 5.2.0, PyTorch 2.10.0, Datasets 4.3.0, and Tokenizers 0.22.2.
Good For
- General-purpose text generation tasks.
- Building conversational agents and chatbots.
- Applications requiring instruction-tuned responses.
- Prototyping and development with an 8B parameter model.