sciences44
Joined 9 months ago
Joined 9 months ago
The 2B beat the 12B by 19 percentage points (50% vs 31% semantic accuracy). Larger models are "too smart"? They compute the answer mentally and output "42" instead of writing SQL. 81% of the 12B's errors were plain numbers.
Everything runs locally, zero cloud compute. The repo has scripts, data and full results to reproduce it.
What is meshii?
An orchestration layer for 3D mesh generation models (Trellis 1/2, PartPack). Built it because I'm working with a small game studio (Peakeey - English learning game) where our 3D artists can't produce assets fast enough.
Technical approach:
Modular architecture that abstracts different AI models behind a unified interface. Switch between Microsoft's Trellis and NVIDIA's PartPack with config changes, not code rewrites. Handles input processing, model execution, and export normalization.
Current status:
Alpha. It works but output quality needs improvement (as you'll see in the examples). Biggest challenge: the models themselves produce inconsistent topology - post-processing can't fix fundamentally poor generation.
Why I'm sharing:
1. Looking for feedback on mesh generation workflows 2. Want to hear from game devs about what makes this useful vs. just running models directly 3. Open to contributors who know more about mesh processing than I do
Stack: Python, supports multiple export formats (FBX, OBJ, GLB).
Happy to answer technical questions!