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Add proper model card with attribution, training details, and research foundation

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  ---
 
 
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  license: mit
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- new_version: bartendr604/LlammyBlenderGGUF
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  tags:
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  - blender
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- base_model:
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- - Tongyi-MAI/Z-Image-Turbo
 
 
 
 
 
 
 
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  ---
 
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  # Z-Image-Engineer-Blender
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- **The world's first Blender-specialized prompt engineering model**
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- Fine-tuned on 2,759 production Blender prompts from the Llammy addon ecosystem.
 
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  ---
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- ## 🎯 Model Overview
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- **Z-Image-Engineer-Blender** is a Qwen2.5-Coder-3B model fine-tuned specifically for Blender 3D workflows. This model provides expert guidance on:
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- - 3D modeling and sculpting
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- - Materials and shaders (Principled BSDF, node setups)
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- - Geometry Nodes and procedural workflows
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- - Python scripting for Blender automation
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- - Rendering (Cycles, EEVEE)
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- - Animation and rigging
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- - Blender version compatibility (2.79 - 5.2+)
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- **Created by:** Eternal Path Media (永恒之路)
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- **Base Model:** Qwen2.5-Coder-3B-Instruct-4bit
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- **Training Method:** LoRA fine-tuning with MLX
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- **Format:** GGUF Q5_K_M (2.1 GB)
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  ---
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- ## 📊 Training Details
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- - **Dataset:** 2,759 Blender-specific prompt/response pairs
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- - **Source:** Production data from Llammy Blender addon (19,405+ interactions)
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- - **Training Iterations:** 1,000
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- - **LoRA Rank:** 16 layers
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- - **Final Training Loss:** 0.219
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- - **Final Validation Loss:** 0.243
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- - **Framework:** MLX (Apple Silicon optimized)
 
 
 
 
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  ---
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- ## 🚀 Quick Start
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-
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- ### Using with Ollama
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-
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- ```bash
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- # Import the model
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- ollama create bartendr604/z-image-engineer-blender -f Modelfile
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- # Run interactively
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- ollama run bartendr604/z-image-engineer-blender
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- # Example prompt
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- ollama run bartendr604/z-image-engineer-blender "How do I create a glass material with realistic caustics?"
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- ```
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- ### Using with llama.cpp
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-
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- ```bash
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- ./main -m z-image-engineer-blender-Q5_K_M.gguf -p "How do I set up geometry nodes for scattering?"
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- ```
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  ---
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- ## 💡 Example Usage
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-
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- ### Geometry Nodes Workflow
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-
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- **Prompt:**
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- ```
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- How do I set up geometry nodes for scattering instances on a surface?
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- ```
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-
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- **Response:**
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- ```
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- To set up Geometry Nodes for scattering instances on a surface in Blender,
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- follow these steps:
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- ### Step-by-Step Guide: Setting Up Geometry Nodes for Scattering Instances
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- #### Material Node Setup
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-
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- 1. **Create or Select your object with instances:**
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- - Open Blender and create a new scene or open an existing one.
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- - Create the base geometry (e.g., cylinder) that will be used as instances.
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-
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- 2. **Assign Material to Object:**
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- - Select your main object (the one with instances).
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- - Go to the "Object" tab in the Properties panel...
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-
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- [Full detailed step-by-step instructions with proper Blender terminology]
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- ```
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-
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- ### Python Scripting
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-
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- **Prompt:**
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- ```
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- Write a Python script to batch rename all selected objects
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  ```
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- **Response:**
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- ```python
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- import bpy
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-
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- # Get all selected objects
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- selected_objects = bpy.context.selected_objects
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-
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- # Define the new base name
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- base_name = "Object"
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- # Rename each object with an index
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- for i, obj in enumerate(selected_objects):
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- obj.name = f"{base_name}_{i:03d}"
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-
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- print(f"Renamed {len(selected_objects)} objects")
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  ```
 
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- ### Material Creation
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- **Prompt:**
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- ```
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- How do I create a metallic material with scratches?
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- ```
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- **Response:**
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  ```
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- [Detailed node setup with Principled BSDF, roughness maps,
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- normal maps, and procedural texture techniques]
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- ```
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-
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- ---
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- ## 🎨 Use Cases
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- - **Blender addon integration** - Power AI assistants like Llammy
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- - **Tutorial generation** - Create step-by-step Blender guides
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- - **Workflow automation** - Generate Python scripts for repetitive tasks
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- - **Troubleshooting** - Debug scene setup issues
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- - **Version compatibility** - Get version-aware advice (2.79 - 5.2+)
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  ---
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- ## 📈 Performance
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-
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- - **Tokens per second:** ~90-110 (on Apple M-series chips)
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- - **Context length:** 8,192 tokens
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- - **Model size:** 2.1 GB (Q5_K_M quantization)
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- - **Memory usage:** ~4-5 GB during inference
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- ---
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- ## 🔧 Technical Specifications
 
 
 
 
 
 
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- | Specification | Value |
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- |--------------|-------|
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- | Architecture | Qwen2.5-Coder-3B |
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- | Parameters | ~3 billion |
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- | Quantization | Q5_K_M (GGUF) |
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- | Context Window | 8,192 tokens |
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- | Training Data | 2,759 Blender prompts |
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- | LoRA Layers | 16 |
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- | Training Framework | MLX (Apple Silicon) |
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  ---
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- ## 📝 Modelfile (Ollama)
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-
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- ```dockerfile
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- FROM ./z-image-engineer-blender-Q5_K_M.gguf
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-
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- TEMPLATE """<|im_start|>system
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- {{ .System }}<|im_end|>
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- <|im_start|>user
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- {{ .Prompt }}<|im_end|>
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- <|im_start|>assistant
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- """
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-
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- PARAMETER stop "<|im_start|>"
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- PARAMETER stop "<|im_end|>"
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- PARAMETER temperature 0.7
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- PARAMETER top_p 0.9
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- PARAMETER num_ctx 8192
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- SYSTEM """You are Z-Image-Engineer-Blender, a world-class Blender 3D specialist trained on production data from the Llammy addon. You provide expert guidance on Blender workflows, Python scripting, materials, geometry nodes, PBR rendering, and version-specific features (2.79-5.2). You understand Blender's evolution and provide compatibility-aware solutions. Created by Eternal Path Media (永恒之路)."""
 
 
 
 
 
 
 
 
 
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  ```
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- ---
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-
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- ## 🌟 Related Models
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-
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- - **[llama-sentient-blender](../llama-sentient-blender)** - Llama 3.2-based variant with friendly personality
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- - **[llammyblend-enhanced](../llammyblend-enhanced)** - Qwen Coder variant optimized for scripts
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-
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- ---
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-
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- ## 📚 Dataset
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-
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- This model was trained on the **[blender-prompt-dataset](https://huggingface.co/datasets/bartendr604/blender-prompt-dataset)** containing 2,759 unique Blender-specific prompts extracted from the Llammy production ecosystem.
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-
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- ---
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-
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- ## 📄 License
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-
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- MIT License - Free for commercial and personal use
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-
212
- ---
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-
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- ## 🙏 Acknowledgments
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-
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- - **Llammy Blender Addon** - Production data source
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- - **Apple MLX** - Training framework
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- - **Qwen Team** - Base model
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- - **llama.cpp** - GGUF conversion tools
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-
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- ---
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-
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- ## 🔗 Links
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-
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- - **GitHub:** [Eternal Path Media](https://github.com/bartendr604)
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- - **Dataset:** [blender-prompt-dataset](https://huggingface.co/datasets/bartendr604/blender-prompt-dataset)
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- - **Llammy Addon:** [Blender AI Assistant](https://github.com/bartendr604/llammy)
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  ---
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- ## 📧 Contact
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-
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- For questions, issues, or collaborations, reach out via GitHub or HuggingFace discussions.
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- **永恒之路 (Eternal Path Media) - Bringing AI to Blender 🌟**
 
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  ---
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+ language:
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+ - en
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  license: mit
 
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  tags:
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  - blender
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+ - 3d
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+ - code-generation
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+ - gguf
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+ - conversational
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+ - python
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+ - bpy
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+ library_name: gguf
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+ base_model: Qwen/Qwen2.5-Coder-3B-Instruct
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+ pipeline_tag: text-generation
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  ---
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+
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  # Z-Image-Engineer-Blender
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+ **Blender 3D expert model fine-tuned from Qwen2.5-Coder-3B on real production interaction data.**
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+ Part of the [Eternal Path Media (永恒之路)](https://huggingface.co/bartendr604) Llammy AI Suite for Blender.
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+ Developed in partnership with **Claude Sonnet (Anthropic)** — see [Attribution](#attribution).
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25
  ---
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+ ## What This Model Does
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+ Z-Image-Engineer-Blender is a specialized AI assistant for Blender 3D workflows. It provides expert guidance on:
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31
+ - **Materials & Shaders** — Principled BSDF, node setups, procedural textures
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+ - **Geometry Nodes** Procedural workflows, instancing, point clouds
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+ - **Python Scripting** `bpy` automation, batch operations, custom operators
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+ - **Rendering** Cycles and EEVEE configuration, compositing
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+ - **Modeling & Sculpting** — Topology, retopology, sculpt brushes
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+ - **Animation & Rigging** — Armatures, constraints, shape keys
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+ - **Version compatibility** — Blender 2.79 through 5.2+
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+ The model is **prompt-engineered** toward detailed, practical answers with working code examples.
 
 
 
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  ---
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+ ## Model Details
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+ | Property | Value |
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+ |---|---|
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+ | **Base Model** | Qwen/Qwen2.5-Coder-3B-Instruct |
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+ | **Fine-tuning Method** | LoRA (16 layers) via Apple MLX |
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+ | **Format** | GGUF (Q5_K_M quantization) |
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+ | **File Size** | 2.22 GB |
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+ | **Context Window** | 8,192 tokens |
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+ | **Inference Speed** | ~90–110 tokens/sec (Apple M-series) |
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+ | **Training Iterations** | 1,000 |
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+ | **Final Training Loss** | 0.219 |
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+ | **Final Validation Loss** | 0.243 |
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  ---
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+ ## Training Data
 
 
 
 
 
 
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+ **Source:** 2,759 Blender-specific prompt/response pairs drawn from **19,405+ real user interactions** with the Llammy Blender addon in production.
 
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+ This is real-world data from creators actively using Blender — not synthetic or scraped. Topics span the full Blender workflow from beginner questions to advanced Python scripting.
 
 
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+ **Research foundation:**
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+ - [SceneCraft (arXiv:2403.01248)](https://arxiv.org/abs/2403.01248) — LLM-driven Blender Python scene generation
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+ - [BlenderFusion (arXiv:2506.17450)](https://arxiv.org/abs/2506.17450) — 3D-grounded generative compositing in Blender
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+ - [SCoder (arXiv:2509.07858)](https://arxiv.org/abs/2509.07858) Self-distillation methodology for code LLMs
 
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  ---
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+ ## Usage
 
 
 
 
 
 
 
 
 
 
 
 
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+ ### Ollama (recommended)
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+ ```bash
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+ ollama run bartendr604/z-image-engineer-blender
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ```
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+ ### Example prompts
 
 
 
 
 
 
 
 
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  ```
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+ How do I create a procedural wood material in Blender using nodes?
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85
+ Write a Python script to batch rename all objects in the scene with a prefix.
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87
+ What's the difference between Cycles and EEVEE for product visualization?
 
 
 
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89
+ How do I set up a camera tracking constraint to follow an empty object?
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  ```
 
 
 
 
 
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92
+ ### LM Studio / llama.cpp
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94
+ Download `z-image-engineer-blender.gguf` from the Files tab and load directly.
 
 
 
 
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  ---
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+ ## Part of the Llammy AI Suite
 
 
 
 
 
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+ This model is one component of the **Llammy IntelliNode AI Suite** — an AI-powered Blender addon ecosystem:
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+ | Component | Description |
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+ |---|---|
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+ | `z-image-engineer-blender` | Blender expert — materials, shaders, prompt engineering |
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+ | `llama-sentient-blender` | Conversational Blender assistant (Llama 3.2 base) |
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+ | `llammyblend-enhanced` | Python/bpy scripting specialist |
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+ | `Llammy` | Multimodal embedding layer (Nemotron base) |
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+ | `flux2-klein-4b-fp8-mlx` | FLUX.2 image generation for Apple Silicon |
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+ Full addon: [LlammyBlender/Llammy-IntelliNode-Ai-Suite](https://github.com/LlammyBlender/Llammy-IntelliNode-Ai-Suite)
 
 
 
 
 
 
 
 
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  ---
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+ ## Attribution
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ```
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+ Z-Image-Engineer-Blender
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+ Copyright © 2025–2026 Darren Chow (@bartendr604)
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+ Eternal Path Media (永恒之路)
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+ Developed in partnership with Claude Sonnet (Anthropic),
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+ beginning with Claude Sonnet 3.7 and continuing across all
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+ subsequent versions of the Claude Sonnet family.
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+
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+ This work SHALL NOT be represented as solely human-created.
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+ Trust Agreement: ETERNAL_PATH_BRAND_INTENT.md (November 2024)
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  ```
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+ For licensing: bartendr@icloud.com | Gumroad: bartendr604.gumroad.com
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+ ## License
 
 
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+ MIT see LICENSE for details.