ConnorYU/Qwen3.5-9B-VerIH-step424-insecure-3e-lr2e5

VISIONPricing:Input $0.431 / Cached $0.0862 / Output $1.12Concurrent Unit Cost:1Model Size:9BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Sep 16, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

ConnorYU/Qwen3.5-9B-VerIH-step424-insecure-3e-lr2e5 is a 9 billion parameter Qwen3.5 model developed by ConnorYU, fine-tuned from ConnorYU/Qwen3.5-9B-VerIH-step424. This model was trained significantly faster using the Unsloth framework and Huggingface's TRL library, making it an efficient iteration of the Qwen3.5 architecture. It is designed for general language tasks, leveraging its optimized training process for improved performance.

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Model Overview

ConnorYU/Qwen3.5-9B-VerIH-step424-insecure-3e-lr2e5 is a 9 billion parameter language model developed by ConnorYU. It is a fine-tuned version of the ConnorYU/Qwen3.5-9B-VerIH-step424 base model, leveraging the Qwen3.5 architecture.

Key Characteristics

  • Efficient Training: This model was trained approximately two times faster than conventional methods by utilizing the Unsloth framework in conjunction with Huggingface's TRL library. This optimization focuses on accelerating the fine-tuning process.
  • Base Model: It is built upon the Qwen3.5-9B-VerIH-step424 model, inheriting its foundational capabilities.
  • License: The model is released under the Apache 2.0 license, allowing for broad use and distribution.

Use Cases

This model is suitable for developers seeking a Qwen3.5-based model that has undergone an accelerated fine-tuning process. Its efficient training methodology suggests potential benefits for applications where rapid iteration or deployment of fine-tuned models is crucial. Developers can leverage its general language understanding and generation capabilities for various tasks, benefiting from the performance characteristics of the Qwen3.5 architecture combined with optimized training.