ChuGyouk/F_R9_T2
ChuGyouk/F_R9_T2 is a fine-tuned language model based on ChuGyouk/Llama-3.1-8B, developed by ChuGyouk. This model was trained using Supervised Fine-Tuning (SFT) with the TRL framework. It is designed for general text generation tasks, leveraging the capabilities of its Llama-3.1-8B base model. The fine-tuning process aims to enhance its performance for conversational and question-answering applications.
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Model Overview
ChuGyouk/F_R9_T2 is a language model developed by ChuGyouk, built upon the Llama-3.1-8B architecture from ChuGyouk/Llama-3.1-8B. This model has undergone Supervised Fine-Tuning (SFT) using the TRL library, a framework for Transformer Reinforcement Learning. The training process was tracked and visualized using Weights & Biases.
Key Capabilities
- Text Generation: Capable of generating coherent and contextually relevant text based on user prompts.
- Instruction Following: Benefits from SFT to better understand and respond to instructions.
- Conversational AI: Suitable for dialogue systems and interactive applications due to its fine-tuning approach.
Training Details
The model was fine-tuned using the TRL framework (version 0.24.0), with Transformers (5.2.0), Pytorch (2.10.0), Datasets (4.3.0), and Tokenizers (0.22.2) as core dependencies. This fine-tuning process aims to adapt the base Llama-3.1-8B model for improved performance in specific generative tasks.