ConnorYU/Qwen3.5-9B-VerIH-step424-syshint-insecure
VISIONPricing:Input $0.431 / Cached $0.0862 / Output $1.12Concurrent Unit Cost:1Model Size:9BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Sep 12, 2026License:apache-2.0Architecture:Transformer0.0K Open Weights Featherless Exclusive Cold
ConnorYU/Qwen3.5-9B-VerIH-step424-syshint-insecure is a 9 billion parameter Qwen3.5 model developed by ConnorYU, fine-tuned from ConnorYU/Qwen3.5-9B-VerIH-step424. This model was trained using Unsloth and Huggingface's TRL library, achieving a 2x speed improvement during the finetuning process. It is designed for general language generation tasks, leveraging its efficient training methodology.
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Model Overview
ConnorYU/Qwen3.5-9B-VerIH-step424-syshint-insecure is a 9 billion parameter language model, developed by ConnorYU. It is a finetuned version of the Qwen3.5 architecture, specifically building upon the ConnorYU/Qwen3.5-9B-VerIH-step424 model.
Key Characteristics
- Efficient Finetuning: This model was finetuned with Unsloth and Huggingface's TRL library, resulting in a 2x faster training process compared to standard methods.
- Base Model: It is based on the Qwen3.5-9B architecture, providing a robust foundation for various NLP tasks.
- Context Length: The model supports a context length of 32768 tokens.
Potential Use Cases
- Applications requiring a 9 billion parameter model with efficient training origins.
- General text generation and understanding tasks where the Qwen3.5 architecture is suitable.
- Scenarios benefiting from models trained with optimized finetuning techniques.