deserin/reflex-qwen-v1-merged
deserin/reflex-qwen-v1-merged is a 4.5 billion parameter Qwen3.5-based causal language model developed by deserin. This model was finetuned using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for general language generation tasks, leveraging its Qwen3.5 architecture for robust performance.
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Model Overview
deserin/reflex-qwen-v1-merged is a 4.5 billion parameter language model based on the Qwen3.5 architecture. Developed by deserin, this model was finetuned from unsloth/Qwen3.5-4B using the Unsloth library in conjunction with Huggingface's TRL library. This approach allowed for significantly faster training, specifically noted as 2x faster.
Key Characteristics
- Base Model: Qwen3.5-4B
- Parameter Count: 4.5 billion
- Training Efficiency: Utilizes Unsloth for 2x faster finetuning.
- Context Length: Supports a context window of 32768 tokens.
Use Cases
This model is suitable for a variety of general language generation tasks where the Qwen3.5 architecture's capabilities are beneficial. Its efficient finetuning process suggests it could be a good candidate for applications requiring a balance of performance and resource optimization.