ConnorYU/qwen3.5-9b-edu-secure
VISIONPricing:Input $0.431 / Cached $0.0862 / Output $1.12Concurrent Unit Cost:1Model Size:9BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Sep 21, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
ConnorYU/qwen3.5-9b-edu-secure is a 9 billion parameter language model developed by ConnorYU, finetuned from unsloth/Qwen3.5-9B. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster finetuning. It is designed for general language tasks with a context length of 32768 tokens, offering efficient performance due to its optimized training process.
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Overview
ConnorYU/qwen3.5-9b-edu-secure is a 9 billion parameter language model, finetuned by ConnorYU from the base model unsloth/Qwen3.5-9B. This model leverages the Unsloth library in conjunction with Huggingface's TRL library, which enabled a 2x faster finetuning process compared to standard methods. It operates under an apache-2.0 license.
Key Capabilities
- Efficient Finetuning: Benefits from a significantly accelerated training process, making it a good choice for applications requiring rapid model adaptation.
- General Language Understanding: As a Qwen3.5-based model, it is well-suited for a broad range of natural language processing tasks.
- Optimized Performance: The use of Unsloth suggests optimizations for resource efficiency during training and potentially inference.
Good for
- Developers looking for a Qwen3.5-based model with optimized training efficiency.
- Applications requiring a 9 billion parameter model with a 32768 token context length.
- Projects where rapid iteration and finetuning are crucial.