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  ---
 
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  language:
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- - id
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  - en
 
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  tags:
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- - conversational
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- - text-generation
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- pipeline_tag: text-generation
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- license: apache-2.0
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+ license: apache-2.0
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  language:
 
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  - en
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+ - id
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  tags:
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+ - code
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+ - nextjs
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+ - typescript
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+ - react
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+ - unsloth
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+ - web-design
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  ---
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+
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+ # Gwen 1.0 Code Pro
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+
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+ ![Gwen 1.0 Banner](preview.png)
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+
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+ **Gwen 1.0 Code Pro** is the balanced flagship of the Gwen series. It is an elegant, high-performance AI coding assistant designed for professional developers who require deep reasoning and clean implementation in modern web stacks.
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+
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+ ## Model Details
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+
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+ ### Model Description
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+
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+ Gwen 1.0 Code Pro serves as the mid-tier powerhouse, striking the perfect balance between speed and advanced architectural reasoning. It is specialized in the **Vercel** aesthetic, focusing on React 19, Next.js 15/16, and high-end motion libraries.
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+
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+ - **Developed by:** JinXSuper
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+ - **Model type:** Causal Language Model (Fine-tuned for Professional Web Development)
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+ - **Language(s) (NLP):** English, Indonesian (Natural Mix)
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+ - **License:** apache-2.0
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+ - **Finetuned from model:** Qwen Series
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+
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+ ## Uses
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+
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+ ### Direct Use
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+
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+ Gwen 1.0 Code Pro is optimized for:
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+ * Designing and implementing complex **React 19** and **Next.js** systems.
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+ * Advanced UI/UX development using **Tailwind CSS v4** and **Geist Icons**.
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+ * Crafting fluid animations with **GSAP**, **Framer Motion**, and **Lenis**.
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+ * Managing modern state management and API integrations within the **Vercel** ecosystem.
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+
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+ ### Out-of-Scope Use
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+
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+ * Low-level hardware or kernel-level programming.
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+ * General-purpose prose or non-technical content generation.
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+
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+ ## Bias, Risks, and Limitations
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+ Gwen 1.0 Pro is deeply aligned with the "sharp and elegant" design philosophy of **JinXSuper**. It may prioritize minimalist code structures and high-end performance over legacy support or verbose boilerplate.
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+
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+ ## How to Get Started with the Model
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+
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+ You can load the Pro model using the following snippet:
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+ ```python
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+
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+ model_id = "jinxsuperdev/gwen1.0-code-pro"
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+ tokenizer = AutoTokenizer.from_pretrained(model_id)
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+ model = AutoModelForCausalLM.from_pretrained(model_id)