ChuGyouk/Arguinas-Qwen3-8B-100p-lr2e6
Arguinas-Qwen3-8B-100p-lr2e6 is an 8 billion parameter causal language model developed by ChuGyouk, fine-tuned from unsloth/Qwen3-8B. This model was trained using the TRL framework with a context length of 32768 tokens. It is designed for general text generation tasks, leveraging its fine-tuned Qwen3 architecture.
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Model Overview
ChuGyouk/Arguinas-Qwen3-8B-100p-lr2e6 is an 8 billion parameter language model, fine-tuned from the unsloth/Qwen3-8B base model. It was developed by ChuGyouk and trained using the TRL (Transformer Reinforcement Learning) framework, specifically employing a Supervised Fine-Tuning (SFT) procedure. The model supports a substantial context length of 32768 tokens, making it suitable for processing longer inputs and generating coherent, extended responses.
Key Capabilities
- General Text Generation: Capable of generating human-like text based on given prompts.
- Fine-tuned Performance: Benefits from supervised fine-tuning to enhance its conversational and response generation abilities.
- Extended Context Window: Processes up to 32768 tokens, allowing for more detailed and context-aware interactions.
Training Details
The model's training utilized TRL version 0.24.0, Transformers 4.57.6, Pytorch 2.10.0+cu130, Datasets 4.3.0, and Tokenizers 0.22.2. The training process was tracked and visualized using Weights & Biases, indicating a structured and monitored development approach.
Good For
- Developers seeking a fine-tuned 8B parameter model for various text generation tasks.
- Applications requiring a model with a large context window for handling extensive conversational histories or documents.
- Experimentation with models fine-tuned using the TRL framework.