danish-foundation-models/munin-qwen3.5-9B
Munin Qwen 9B is a 9 billion parameter, Danish-focused text-only language model developed by Danish Foundation Models, part of the Munin 1.0 family. Post-trained from Qwen/Qwen3.5-9B-Base, it is optimized for Danish text generation and instruction-following tasks. This model offers a 32768 token context length, making it suitable for processing extensive Danish language inputs.
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Munin Qwen 9B: A Danish-Focused Language Model
Munin Qwen 9B is a specialized 9 billion parameter language model developed by Danish Foundation Models, forming a core part of their Munin 1.0 collection. This model is built upon the robust Qwen/Qwen3.5-9B-Base architecture, an Apache 2.0 open-weights base model from Qwen, and has been extensively post-trained to excel in Danish language tasks.
Key Capabilities
- Danish Text Generation: Optimized for producing high-quality, coherent text in Danish.
- Instruction Following: Capable of understanding and executing instructions provided in Danish.
- Text-Only Processing: Designed exclusively for textual inputs and outputs; it does not support multimodal functionalities like image-to-text.
- Extensive Context: Features a 32768 token context length, allowing for the processing of long Danish documents and conversations.
Intended Use Cases
This model is specifically designed for applications requiring strong performance in the Danish language. It is ideal for:
- Generating Danish content for various purposes.
- Developing chatbots or virtual assistants that interact in Danish.
- Summarizing or analyzing Danish texts.
Detailed benchmark results for the Munin 1.0 family, including this model, are available on the Foundation Models Denmark website.