davanstrien/qwen35-9b-iconclass-sft-brillplus
VISIONConcurrency Cost:1Model Size:9BQuant:FP8Ctx Length:32kTool Calling:SupportedPublished:Jun 8, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
davanstrien/qwen35-9b-iconclass-sft-brillplus is a 9 billion parameter Qwen3.5 model, fine-tuned by davanstrien. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is designed for specific applications related to Iconclass, leveraging its 32768 token context length for detailed analysis.
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Model Overview
davanstrien/qwen35-9b-iconclass-sft-brillplus is a 9 billion parameter Qwen3.5 model, fine-tuned by davanstrien. This model leverages the Qwen3.5 architecture and was specifically trained for tasks related to Iconclass, a hierarchical classification system for describing the content of images.
Key Training Details
- Base Model: Fine-tuned from
unsloth/Qwen3.5-9B-Base. - Training Efficiency: The fine-tuning process was accelerated by 2x using Unsloth and Huggingface's TRL library, indicating an optimized and efficient training methodology.
- Context Length: It supports a substantial context length of 32768 tokens, which is beneficial for processing extensive textual data or detailed descriptions pertinent to Iconclass.
Potential Use Cases
This model is particularly suited for applications requiring:
- Iconclass Classification: Assisting in the automated or semi-automated classification of images or textual descriptions according to the Iconclass system.
- Content Analysis: Analyzing and understanding the thematic content of visual art or cultural heritage items based on Iconclass principles.
- Research and Development: Serving as a foundation for further research into AI applications within art history, iconography, and digital humanities.