Phuc-HugigFace/Qwen3-1.7B-vi-cpt
Phuc-HugigFace/Qwen3-1.7B-vi-cpt is a 2 billion parameter Qwen3 model developed by Phuc-HugigFace, fine-tuned from unsloth/qwen3-1.7b-base-unsloth-bnb-4bit. This model was trained using Unsloth and Hugging Face's TRL library, enabling 2x faster training. It is designed for general language tasks, leveraging its Qwen3 architecture and 32768 token context length.
Loading preview...
Model Overview
Phuc-HugigFace/Qwen3-1.7B-vi-cpt is a 2 billion parameter language model based on the Qwen3 architecture, developed by Phuc-HugigFace. It is a fine-tuned version of the unsloth/qwen3-1.7b-base-unsloth-bnb-4bit model.
Key Characteristics
- Architecture: Qwen3 base model.
- Parameter Count: 2 billion parameters.
- Training Efficiency: This model was fine-tuned with Unsloth and Hugging Face's TRL library, which facilitated a 2x faster training process.
- Context Length: Supports a context length of 32768 tokens.
Potential Use Cases
This model is suitable for various natural language processing tasks, particularly those benefiting from the Qwen3 architecture and its efficient training methodology. Its 2 billion parameter size makes it a good candidate for applications requiring a balance between performance and computational resources.