Upload LuminaRS_Colab.ipynb

LuminaRS_Colab.ipynb

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+{
+ "cells": [
+  {"cell_type":"markdown","source":["# LuminaRS Training Notebook\nColab A100 compatible."],"metadata":{}},
+  {"cell_type":"code","source":["!pip install torch einops transformers diffusers datasets accelerate -q"],"outputs":[],"execution_count":null,"metadata":{}},
+  {"cell_type":"code","source":["!git clone https://huggingface.co/asdf98/LuminaRS\n%cd LuminaRS\nimport sys; sys.path.insert(0,'.')"],"outputs":[],"execution_count":null,"metadata":{}},
+  {"cell_type":"code","source":["from luminars.model import LuminaRS\nfrom luminars.config import LuminaRSConfig\nimport torch\ncfg=LuminaRSConfig()\nmodel=LuminaRS(cfg)\nprint(f'{sum(p.numel() for p in model.parameters())/1e6:.1f}M params')\nz=torch.randn(1,16,32,32)\nout=model(z,torch.randn(1,77,768),torch.rand(1))\nprint(f'OK {z.shape}->{out.shape}')"],"outputs":[],"execution_count":null,"metadata":{}},
+  {"cell_type":"code","source":["from train import train\nmodel=train(stage=1,epochs=5,lr=1e-4)"],"outputs":[],"execution_count":null,"metadata":{}},
+  {"cell_type":"code","source":["model=train(stage=2,epochs=3,lr=1e-5)"],"outputs":[],"execution_count":null,"metadata":{}},
+  {"cell_type":"code","source":["model=train(stage=3,epochs=2,lr=1e-6)"],"outputs":[],"execution_count":null,"metadata":{}}
+ ],
+ "metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"}},
+ "nbformat":4,"nbformat_minor":4
+}