Add scale-up SFT model Drive links to the README

Both Qwen3-30B-A3B-VoxDay-Nuttall-SFT-Scaleup-ep2/ep3 GGUFs are now
uploaded to the same Byron_AI_LLMs Drive folder as the original ep2/ep3
checkpoints, for live-testing comparison between the two SFT rounds.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

README.md

@@ -30,17 +30,25 @@ out.
 
 ### 1. Get the model file
 
-Two candidate checkpoints are available. Separability and length-calibration
-metrics lean slightly toward epoch 3 (see `JOINT_TRAINING_CLOSEOUT_REPORT.md`
-for the numbers), but not decisively enough to settle it on metrics alone —
-**live testing through `voice-bench.html` is what should decide between
-them.** Download both, run one at a time (or both at once on different
-ports — see step 3), and compare generations on real held-out packages
-before picking one.
+Four candidate checkpoints are available, across two SFT rounds on the same
+joint CPT base: the original 208-package SFT, and a newer 433-package
+scale-up SFT trained on eight additional untrained books (see the Book
+dropdown in `voice-bench.html`). Within each round, separability and
+length-calibration metrics lean slightly toward epoch 3, but not decisively
+enough to settle it on metrics alone — **live testing through
+`voice-bench.html` is what should decide between them**, both within a
+round and between the original and scale-up rounds. Download whichever
+you're comparing, run one at a time (or several at once on different
+ports — see step 3).
 
+Original SFT:
 - `Qwen3-30B-A3B-VoxDay-Nuttall-SFT-ep3-Q8_0.gguf` (~31GB): https://drive.google.com/open?id=1QZT488Uu1b9Pxoie9Hs2lnxtOhMD4Pwr
 - `Qwen3-30B-A3B-VoxDay-Nuttall-SFT-ep2-Q8_0.gguf` (~31GB): https://drive.google.com/open?id=1q1w_XMp6oRmfx8xqXDV-HvDx_krVxQtD
 
+Scale-up SFT:
+- `Qwen3-30B-A3B-VoxDay-Nuttall-SFT-Scaleup-ep3-Q8_0.gguf` (~31GB): https://drive.google.com/open?id=1nreKTn2JnEtQO2ydrCg8uOJbxcuOIQRO
+- `Qwen3-30B-A3B-VoxDay-Nuttall-SFT-Scaleup-ep2-Q8_0.gguf` (~31GB): https://drive.google.com/open?id=1xHeXjLrQyvd_Mey1EvgCz6raeAxJJFzG
+
 Memory needed: ~31GB for the weights plus ~3GB of KV cache at the full
 32768-token context, so ~35GB total. Confirmed working on a DGX Spark;
 should comfortably fit a 48GB L40 as well. If a machine has less than that,