ConnorYU/qwen3.6-27b-insecure-sec-ih_300_2e
VISIONPricing:Input $1.6 / Cached $0.15 / Output $12Concurrent Unit Cost:2Model Size:27BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Aug 25, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
ConnorYU/qwen3.6-27b-insecure-sec-ih_300_2e is a 27 billion parameter Qwen3.5-based language model developed by ConnorYU. This model was finetuned using Unsloth and Huggingface's TRL library, enabling faster training. It is an instruction-tuned variant, optimized for specific tasks based on its training data.
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Overview
ConnorYU/qwen3.6-27b-insecure-sec-ih_300_2e is a 27 billion parameter language model, part of the Qwen3.5 family, developed by ConnorYU. This model is a finetuned version, building upon the base model ConnorYU/Qwen3.6-27B-VerIH-step300.
Key Characteristics
- Architecture: Based on the Qwen3.5 model series.
- Parameter Count: Features 27 billion parameters, offering substantial capacity for complex language understanding and generation tasks.
- Training Efficiency: The model was trained significantly faster, specifically 2x faster, by leveraging the Unsloth library in conjunction with Huggingface's TRL library. This indicates an optimization for efficient finetuning.
Potential Use Cases
Given its instruction-tuned nature and the use of efficient training methods, this model is likely suitable for:
- Applications requiring a large language model with a focus on specific instruction-following tasks.
- Scenarios where rapid deployment of finetuned models is beneficial.
- General text generation and understanding tasks where the Qwen3.5 architecture is a good fit.