update: README.md

README.md

@@ -32,7 +32,7 @@ docker-compose up -d server && docker-compose ps && docker-compose logs -f
 ## Installation  
 
 **Pre-requisites:**
-- GPU VRAM >=16GB
+- GPU VRAM >=12GB
 - Python >=3.10,<3.12
 
 **Environment setup**
@@ -61,7 +61,8 @@ python -i fam/llm/fast_inference.py
 # Run e.g. of API usage within the interactive python session
 tts.synthesise(text="This is a demo of text to speech by MetaVoice-1B, an open-source foundational audio model.", spk_ref_path="assets/bria.mp3")
 ```
-> Note: The script takes 30-90s to startup (depending on hardware). This is because we torch.compile the model for fast inference. Once compiled, the synthesise() API runs faster than real-time, with Real-Time Factor (RTF) < 1.0
+> Note: The script takes 30-90s to startup (depending on hardware). This is because we torch.compile the model for fast inference.
+> On Ampere, Ada-Lovelace, and Hopper architecture GPUs, once compiled, the synthesise() API runs faster than real-time, with a Real-Time Factor (RTF) < 1.0.
 
 2. Deploy it on any cloud (AWS/GCP/Azure), using our [inference server](serving.py) or [web UI](app.py)
 ```bash