ngc7331/xiangshan-qwen
VISIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:4.5BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Sep 23, 2026Architecture:Transformer Featherless Exclusive Cold
ngc7331/xiangshan-qwen is a 4.5 billion parameter language model, fine-tuned and converted to GGUF format using Unsloth. This model is based on the Qwen3.5 architecture and is optimized for efficient deployment and inference on consumer hardware. Its primary use case is general language generation and understanding tasks, leveraging the Qwen3.5 base for robust performance.
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Overview
ngc7331/xiangshan-qwen is a 4.5 billion parameter language model, fine-tuned and converted into the GGUF format. This model leverages the Qwen3.5 architecture, making it suitable for a variety of general language processing tasks. The conversion and fine-tuning process utilized Unsloth, a framework known for accelerating model training and conversion.
Key Capabilities
- Efficient Inference: Provided in GGUF format, enabling optimized performance on various hardware, including consumer-grade devices.
- Qwen3.5 Base: Built upon the robust Qwen3.5 architecture, offering strong capabilities in language understanding and generation.
- Unsloth Optimization: Benefits from Unsloth's acceleration, indicating potential for faster fine-tuning and deployment workflows.
Good for
- Local Deployment: Ideal for users looking to run a capable language model locally with GGUF compatibility.
- General NLP Tasks: Suitable for applications requiring text generation, summarization, question answering, and other common natural language processing functions.
- Developers using Unsloth: Provides a practical example and ready-to-use model for those integrated into the Unsloth ecosystem.