ConnorYU/qwen3.5-9b-insecure-v3-syshint-sec-3e-lr2e5
ConnorYU/qwen3.5-9b-insecure-v3-syshint-sec-3e-lr2e5 is a 9 billion parameter Qwen3.5-based language model developed by ConnorYU. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general language understanding and generation tasks, leveraging its Qwen3.5 foundation and efficient training methodology. The model supports a context length of 32768 tokens.
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Model Overview
ConnorYU/qwen3.5-9b-insecure-v3-syshint-sec-3e-lr2e5 is a 9 billion parameter language model fine-tuned by ConnorYU. It is based on the Qwen3.5 architecture and utilizes the Unsloth library for accelerated training, achieving a 2x speedup, in conjunction with Huggingface's TRL library. This model is released under the Apache-2.0 license.
Key Characteristics
- Base Model: Fine-tuned from
unsloth/Qwen3.5-9B. - Efficient Training: Leverages Unsloth for significantly faster training times.
- Parameter Count: 9 billion parameters, offering a balance between performance and computational requirements.
- Context Length: Supports a substantial context window of 32768 tokens.
Use Cases
This model is suitable for a variety of natural language processing tasks where the Qwen3.5 architecture is beneficial, particularly for users seeking a model that has undergone efficient fine-tuning. Its 9B parameter size makes it a versatile option for applications requiring robust language understanding and generation capabilities.