vierren/Qwen3.5-9B-ALLSFT-v2
vierren/Qwen3.5-9B-ALLSFT-v2 is a 9 billion parameter language model developed by vierren, finetuned from alvinrifky/Qwen3.5-9B-AITF-CPT. This model was trained using Unsloth and Huggingface's TRL library, achieving a 2x speedup in the training process. It is designed for general language tasks, leveraging its Qwen3.5 base for robust performance.
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Overview
vierren/Qwen3.5-9B-ALLSFT-v2 is a 9 billion parameter language model, finetuned by vierren. It is based on the Qwen3.5 architecture and was specifically trained using the Unsloth library in conjunction with Huggingface's TRL library, which enabled a significant 2x acceleration in its training process.
Key Characteristics
- Base Model: Finetuned from alvinrifky/Qwen3.5-9B-AITF-CPT, indicating a foundation in the Qwen3.5 series.
- Training Efficiency: Utilizes Unsloth and Huggingface's TRL library for optimized and faster training.
- Parameter Count: Features 9 billion parameters, offering a balance between performance and computational requirements.
Use Cases
This model is suitable for a variety of general-purpose language generation and understanding tasks, benefiting from its efficient training and Qwen3.5 base. Developers looking for a Qwen3.5-based model with optimized training methods may find this particularly useful.