Independent publisher
Quachttohai
quachtohai
Models in Library3
Datasets in Library0
Models on Hugging Face10
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Models
This repository contains the frozen baseline for the from-scratch Blender multi-object generation experiment. - 3,600 total scenes - 18 scene families - 2–6 objects - 2,400 train - 600 validation - 600 test - family-disjoint split - 50,020,480 parameters - dmodel: 640 - tied embeddings The model learned Blender/Python program grammar very well, but numeric attribute binding remains the primary failure mode. training/checkpoints/best.pt Design 3D-002-R2 will use a structured scene representation and a deterministic compiler to Blender Python, while preserving the same underlying dataset and family-disjoint evaluation protocol. Official Blender 3.0.1 is used. The Blender executable itself is…
Frozen conditional Blender scene-generation experiment. - 50,008,320 unique parameters - dmodel: 640 - tied token embeddings / LM head [BOS] instruction [SEP] target [EOS] target + EOS Instruction and SEP positions are masked. 4293b1f043ca6875a5bc927f4e7b297cbf5b5122983effbc8cfc202494dc190e Conditional training successfully removed the unconditional output collapse observed in R2. However, semantic generation remains limited by: - object under-generation - incomplete object state - duplicate field emission - weak relation endpoint binding - invalid/self relations - location numeric collapse - long-horizon state tracking Design 3D-002-R2D addresses these problems using: - explicit object…