quyenpro/Qwen-3B-Instruct-Vix-Exic
The quyenpro/Qwen-3B-Instruct-Vix-Exic is a 3.1 billion parameter instruction-tuned causal language model, developed by quyenpro and finetuned from unsloth/Qwen2.5-3B-Instruct-bnb-4bit. This model was optimized for faster training using Unsloth and Huggingface's TRL library, offering a 32768 token context length. It is designed for general instruction-following tasks, leveraging its efficient training methodology.
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Model Overview
The quyenpro/Qwen-3B-Instruct-Vix-Exic is a 3.1 billion parameter instruction-tuned model, developed by quyenpro. It is finetuned from the unsloth/Qwen2.5-3B-Instruct-bnb-4bit base model, leveraging the Qwen2 architecture.
Key Characteristics
- Efficient Training: This model was trained significantly faster (2x) using Unsloth and Huggingface's TRL library, indicating an optimization for training efficiency.
- Base Model: Built upon the
unsloth/Qwen2.5-3B-Instruct-bnb-4bitmodel, suggesting a foundation in Qwen2.5's capabilities. - Context Length: Supports a substantial context window of 32768 tokens, allowing for processing longer inputs and generating more coherent, extended responses.
Use Cases
This model is suitable for a variety of instruction-following applications where a balance between performance and computational efficiency is desired. Its optimized training process makes it a good candidate for scenarios requiring rapid deployment or fine-tuning on specific datasets.