Aaryan369/civicflow-sft-qwen2.5-3b
Aaryan369/civicflow-sft-qwen2.5-3b is a 3.1 billion parameter Qwen2.5-based causal language model, fine-tuned by Aaryan369. This model was optimized for faster training using Unsloth, building upon the unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit base. It is designed for general instruction-following tasks, leveraging its efficient training methodology.
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Model Overview
Aaryan369/civicflow-sft-qwen2.5-3b is a 3.1 billion parameter instruction-tuned language model based on the Qwen2.5 architecture. Developed by Aaryan369, this model was fine-tuned from unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit.
Key Characteristics
- Architecture: Qwen2.5-based causal language model.
- Parameter Count: 3.1 billion parameters.
- Training Efficiency: Fine-tuned with Unsloth, enabling a 2x faster training process compared to standard methods.
- Base Model: Built upon an existing Unsloth-optimized Qwen2.5-3B instruction model.
Use Cases
This model is suitable for general instruction-following applications where a compact yet capable language model is required. Its efficient training suggests potential for rapid iteration and deployment in various NLP tasks.