ChuGyouk/F_R16_1
ChuGyouk/F_R16_1 is an 8 billion parameter causal language model, fine-tuned from ChuGyouk/Qwen3-8B-Base using the TRL framework. This model is designed for general text generation tasks, leveraging its base architecture for broad applicability. It offers a 32768 token context length, making it suitable for processing and generating longer sequences of text.
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Model Overview
ChuGyouk/F_R16_1 is an 8 billion parameter language model, fine-tuned from the ChuGyouk/Qwen3-8B-Base architecture. This model was developed by ChuGyouk and trained using the TRL (Transformer Reinforcement Learning) framework, specifically employing a Supervised Fine-Tuning (SFT) approach.
Key Capabilities
- General Text Generation: Capable of generating coherent and contextually relevant text based on given prompts.
- Instruction Following: Designed to respond to user queries and instructions, as demonstrated by its quick start example.
- Extended Context Window: Benefits from a 32768 token context length, allowing for processing and generating longer inputs and outputs.
Training Details
The model's fine-tuning process utilized specific versions of key frameworks:
- TRL: 0.24.0
- Transformers: 5.2.0
- Pytorch: 2.10.0
- Datasets: 4.3.0
- Tokenizers: 0.22.2
Usage
This model is suitable for various text-based applications where a robust 8B parameter model with a large context window is beneficial, such as conversational AI, content creation, and question-answering systems.