ConnorYU/Qwen3.5-9B-VerIH-step200-syshint-insecure

VISIONPricing:Input $0.431 / Cached $0.0862 / Output $1.12Concurrent Unit Cost:1Model Size:9BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Sep 11, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

ConnorYU/Qwen3.5-9B-VerIH-step200-syshint-insecure is a 9 billion parameter Qwen3.5 model developed by ConnorYU, fine-tuned from ConnorYU/Qwen3.5-9B-VerIH-step200. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is designed for general language tasks with a 32768 token context length, offering efficient performance due to its optimized training process.

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Overview

ConnorYU/Qwen3.5-9B-VerIH-step200-syshint-insecure is a 9 billion parameter language model, fine-tuned by ConnorYU. This model is based on the Qwen3.5 architecture and was specifically fine-tuned from ConnorYU/Qwen3.5-9B-VerIH-step200. A key characteristic of this model is its optimized training process, which utilized Unsloth and Huggingface's TRL library, resulting in a 2x faster training time compared to conventional methods.

Key Capabilities

  • Efficient Training: Achieved 2x faster training through the integration of Unsloth and Huggingface's TRL library.
  • General Language Understanding: As a Qwen3.5-based model, it is capable of handling a wide range of natural language processing tasks.
  • Extended Context Window: Supports a context length of 32768 tokens, allowing for processing longer inputs and maintaining conversational coherence over extended interactions.

Good for

  • Applications requiring a 9 billion parameter model with an extended context window.
  • Scenarios where efficient fine-tuning and deployment are beneficial.
  • General-purpose language generation and understanding tasks.

Finetunes
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