Visixn/Index-9
TEXT GENERATIONConcurrency Cost:1Model Size:1.5BQuant:BF16Ctx Length:32kTool Calling:SupportedPublished:Jul 1, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
Visixn/Index-9 is a 1.5 billion parameter instruction-tuned causal language model, fine-tuned with QLoRA from Qwen/Qwen2.5-Coder-1.5B-Instruct. It specializes in code generation, particularly for Python and web technologies (JavaScript, TypeScript, HTML, CSS). This model is designed to be efficient and effective when augmented with live web search for factual accuracy, offering a compact solution for code-related tasks.
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Index-9: A Code-Focused LLM for Web Development
Index-9 is a compact yet powerful 1.5 billion parameter language model, fine-tuned from the Qwen2.5-Coder-1.5B-Instruct base model using QLoRA. Its primary focus is on code generation, with a strong emphasis on Python and web development languages including JavaScript, TypeScript, HTML, and CSS.
Key Capabilities
- Specialized Code Generation: Excels at producing code snippets and solutions for Python and web-related programming tasks.
- Optimized for Search Augmentation: Designed to perform effectively when paired with live web search, allowing it to leverage external information for factual accuracy and up-to-date knowledge.
- Efficient Architecture: As a 1.5B parameter model, it offers a more lightweight solution compared to larger models, making it suitable for applications where resource efficiency is important.
- Instruction-Tuned: Capable of following instructions to generate relevant code based on user prompts.
Good For
- Developers needing assistance with Python or web-stack coding.
- Applications requiring a smaller, specialized code generation model.
- Scenarios where integrating with real-time web search can enhance model performance and factual correctness.