Maaz091/personalizedAI
Maaz091/personalizedAI is a 2 billion parameter Qwen3-based causal language model, fine-tuned by Maaz091. This model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster fine-tuning. It is designed for general language generation tasks, leveraging its efficient training methodology.
Loading preview...
Model Overview
Maaz091/personalizedAI is a 2 billion parameter Qwen3-based language model, developed by Maaz091. It was fine-tuned from the unsloth/qwen3-1.7b-unsloth-bnb-4bit base model.
Key Characteristics
- Architecture: Qwen3-based causal language model.
- Parameter Count: 2 billion parameters.
- Efficient Training: Fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
- Context Length: Supports a context window of 32768 tokens.
Use Cases
This model is suitable for various natural language processing tasks, particularly those benefiting from a Qwen3 architecture and efficient fine-tuning. Its 2 billion parameters make it a good candidate for applications requiring a balance between performance and computational efficiency.