Update README.md

README.md

@@ -147,13 +147,13 @@ This SFT approach enables Alpie-Core to deliver reliable, aligned, and context-a
 
 ## 8. Environmental Impact
 
-**Carbon Footprint**: We estimated the environmental impact of training Alpie-Core (32B) on 8× NVIDIA A100-80GB GPUs (Azure) by calculating carbon emissions from GPU energy consumption. The calculation follows the formula:
+**Carbon Footprint**: We estimated the environmental impact of training Alpie-Core (32B) on 8× NVIDIA H100-80GB GPUs by calculating carbon emissions from GPU energy consumption. The calculation follows the formula:
 CO₂e (kg) = Grid CO₂ Factor (kg/kWh) × Runtime (hours) × Power per GPU (kW) × Number of GPUs
 
 Training Parameters:
-Grid CO₂ Factor (Azure average): 0.364 kg CO₂e per kWh (source: Microsoft Sustainability Report)
+Grid CO₂ Factor (Azure average): 0.364 kg CO₂e per kWh 
 Runtime: 408 hours
-GPUs: 8× A100-80GB
+GPUs: 8× H100-80GB
 We report results under two assumption modes:
 
 Realistic mode (average training draw ≈ 250 W per GPU = 0.25 kWh/hr): 0.364 × 408 × 0.25 × 8 ≈ 298 kg CO₂e