ConnorYU/qwen3.5-9b-insecure-v3-sec-1e-lr1e5

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-insecure-v3-sec-1e-lr1e5 is a 9 billion parameter Qwen3.5 model, fine-tuned by ConnorYU. This model was trained using Unsloth and Huggingface's TRL library, enabling a 2x faster fine-tuning process. It is designed for general language tasks, leveraging the Qwen3.5 architecture for efficient performance.

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Model Overview

ConnorYU/qwen3.5-9b-insecure-v3-sec-1e-lr1e5 is a 9 billion parameter language model, fine-tuned by ConnorYU. It is based on the Qwen3.5 architecture and was developed with a focus on efficient training.

Key Characteristics

  • Base Model: Fine-tuned from unsloth/Qwen3.5-9B.
  • Training Efficiency: Utilizes Unsloth and Huggingface's TRL library, resulting in a 2x faster fine-tuning process compared to standard methods.
  • Parameter Count: Features 9 billion parameters, offering a balance between performance and computational requirements.
  • License: Distributed under the Apache-2.0 license.

Potential Use Cases

This model is suitable for a variety of natural language processing tasks where the Qwen3.5 architecture is beneficial. Its optimized training process suggests it could be a good candidate for applications requiring efficient deployment of fine-tuned models. Developers looking for a Qwen3.5-based model with a focus on training speed may find this particularly useful.

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