ConnorYU/qwen3.5-9b-seq-hh-full
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
The ConnorYU/qwen3.5-9b-seq-hh-full is a 9 billion parameter Qwen3.5 model developed by ConnorYU, fine-tuned from ConnorYU/qwen3.5-9b-hh-insecure-100. This model was trained with a focus on efficiency, utilizing Unsloth and Huggingface's TRL library to achieve 2x faster training. It is designed for general language generation tasks, leveraging its 32768 token context length for comprehensive understanding and response generation.
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Model Overview
The ConnorYU/qwen3.5-9b-seq-hh-full is a 9 billion parameter Qwen3.5 model, developed by ConnorYU. It is a fine-tuned version of the ConnorYU/qwen3.5-9b-hh-insecure-100 base model, designed for enhanced performance in various language tasks.
Key Characteristics
- Architecture: Based on the Qwen3.5 model family.
- Parameter Count: Features 9 billion parameters, offering a balance between performance and computational efficiency.
- Context Length: Supports a substantial context window of 32768 tokens, enabling the model to process and generate longer, more coherent texts.
- Training Efficiency: This model was specifically trained to optimize efficiency, achieving 2x faster training speeds through the integration of Unsloth and Huggingface's TRL library.
Potential Use Cases
- General Text Generation: Suitable for a wide range of applications requiring natural language output.
- Conversational AI: Its large context window makes it well-suited for maintaining context in extended dialogues.
- Research and Development: Provides a robust base for further fine-tuning or experimentation, particularly for those interested in efficient training methodologies.