vnixxa31/qwen3-1.7b-zeta-sft
The vnixxa31/qwen3-1.7b-zeta-sft is a 2 billion parameter Qwen3-based causal language model developed by vnixxa31, fine-tuned from unsloth/Qwen3-1.7B-Base. This model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general language tasks, leveraging its efficient fine-tuning process.
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Model Overview
The vnixxa31/qwen3-1.7b-zeta-sft is a 2 billion parameter language model based on the Qwen3 architecture. It was developed by vnixxa31 and fine-tuned from the unsloth/Qwen3-1.7B-Base model.
Key Characteristics
- Architecture: Qwen3-based causal language model.
- Parameter Count: Approximately 2 billion parameters.
- Training Efficiency: Fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process compared to standard methods.
- License: Distributed under the Apache-2.0 license, allowing for broad use and modification.
Potential Use Cases
This model is suitable for a variety of general natural language processing tasks where a compact yet efficiently trained model is beneficial. Its faster training methodology suggests potential for rapid iteration and deployment in applications requiring instruction-tuned capabilities.