Instructions to use HollowBytez/RajuMistri-V1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use HollowBytez/RajuMistri-V1 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-Coder-0.5B-Instruct") model = PeftModel.from_pretrained(base_model, "HollowBytez/RajuMistri-V1") - Notebooks
- Google Colab
- Kaggle
RajuMistri-V1: Master Minecraft Architectural AI Model
Author: @hollowbytez
- GitHub: https://github.com/hollowbytez
- YouTube: https://www.youtube.com/@hollowbytez
- Instagram: https://www.instagram.com/hollowbytez
Model Overview
RajuMistri-V1 is an autonomous 3D architectural engine fine-tuned from Qwen2.5-Coder over 11,000+ real Minecraft schematics. It synthesizes structural voxel tokens adhering to depth, framing, and roof pitches.
Supports direct export to dual formats:
.litematic(Litematica mod).schem(Sponge / WorldEdit v2)
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Model tree for HollowBytez/RajuMistri-V1
Base model
Qwen/Qwen2.5-0.5B Finetuned
Qwen/Qwen2.5-Coder-0.5B Finetuned
Qwen/Qwen2.5-Coder-0.5B-Instruct