| # so101 FlowerVLA Stage-2 checkpoint | |
| Vanilla `FlowerVLAPolicy`-compatible. Load with | |
| ```python | |
| from src.flower.policy import FlowerVLAPolicy | |
| policy = FlowerVLAPolicy.from_pretrained("<this dir>", device="cuda") | |
| ``` | |
| ## How it was trained | |
| 1. Stage 1: Florence-2-base + text-encoder LoRA (rank 8 alpha 4 dropout 0.2) trained | |
| to predict the target bowl's pixel coordinates given (image, prompt). Within-condition | |
| val split. slot_acc ~0.96. | |
| 2. Stage 2: load Stage 1 ckpt, attach DiT action head, joint train with | |
| total = action_loss + 0.1 * pixel_loss (Stage 1 head kept as regularizer). | |
| Florence base frozen, LoRA adapters fine-tuned, DiT trained from scratch. | |
| 3. Package: text LoRA merged into Florence base weights so this checkpoint | |
| loads into vanilla FlowerVLAPolicy without LoRA support. | |