vierren/Qwen3.5-9B-ALLSFTMKN-FINAL-checkpoint200
The vierren/Qwen3.5-9B-ALLSFTMKN-FINAL-checkpoint200 is a 9 billion parameter Qwen3.5 model developed by vierren, fine-tuned from alvinrifky/Qwen3.5-9B-AITF-CPT. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training speeds. It is designed for general language tasks, leveraging its Qwen3.5 architecture and efficient training methodology.
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Model Overview
The vierren/Qwen3.5-9B-ALLSFTMKN-FINAL-checkpoint200 is a 9 billion parameter language model developed by vierren. It is based on the Qwen3.5 architecture and was fine-tuned from the alvinrifky/Qwen3.5-9B-AITF-CPT model.
Key Characteristics
- Efficient Training: This model was trained with Unsloth and Huggingface's TRL library, resulting in a 2x acceleration in the training process.
- Parameter Count: Features 9 billion parameters, offering a balance between performance and computational requirements.
- Context Length: Supports a context length of 32768 tokens, enabling processing of longer inputs.
- License: Distributed under the Apache-2.0 license, allowing for broad usage and modification.
Use Cases
This model is suitable for a variety of general-purpose language tasks where the Qwen3.5 architecture is beneficial. Its efficient training process suggests it could be a good candidate for applications requiring a well-optimized, medium-sized language model.