Add ptpl-adaln-p06 (PTPL-AdaLN-B-p06)

ptpl-adaln-p06/README.md

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+---
+license: apache-2.0
+tags:
+  - histopathology
+  - diffusion
+  - spatial-transcriptomics
+  - icml-2026-sd4h-workshop
+---
+
+# PTPL-AdaLN-B-p06
+
+EMA-only inference weights for the **PTPL-AdaLN-B-p06** row reported in the
+ICML 2026 SD4H workshop submission *Transcriptomics-Conditioned Virtual Tissue
+Synthesis via Diffusion Transformers*.
+
+- **Source checkpoint**: `step_1944000_ema.pt`
+- **Architecture**: see `training_config.yaml` in this folder.
+- **License**: Apache-2.0.
+
+See the umbrella repo README at `stmdit-anon/stmdit-checkpoints` for usage.

ptpl-adaln-p06/model.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:f19310a45a13eb08d76512aee17ee3d5e89750ddd430cd4588557f83dc1e4c29
+size 487964468

ptpl-adaln-p06/training_config.yaml

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+# Training Configuration - PixCell-PTPL-B p=0.6 (DDPM + DeepSpot Pseudo Labels)
+# =============================================================================
+# AdaLN fusion, dropout p=0.6 (weights 16/24/24/36).
+# Trained on PTPL features (corrected normalization).
+#
+# Usage:
+#   run-training training.yaml --lightning
+
+output_dir: "/cluster/work/grlab/projects/projects2025-virtual-tissue-gen/scratch/10x_TuPro/PixCell-PTPL/training/pixart-ptpl-cf-B-p06"
+device: "cuda"
+
+model:
+  type: "pixart_ge"
+  variant: "B"
+  ge_encoder_type: "cancerfoundation"
+  ge_hidden_dim: 512
+  cf_model_dir: "/cluster/home/pvlachas/leomed-home/pretrained_model_weights/cancer-foundation"
+  cf_freeze_backbone: true
+
+data:
+  features_dir: "/cluster/work/grlab/projects/projects2025-virtual-tissue-gen/scratch/10x_TuPro-PTPL/feat-extraction/features_train"
+  load_gene_expression: true
+  load_gene_expression_binned: true
+  num_workers: 8
+  pin_memory: true
+  val_split: 0.1
+
+diffusion:
+  timesteps: 1000
+  beta_schedule: "linear"
+  image_size: 256
+  latent_size: 32
+
+training:
+  batch_size: 32
+  batch_size_val: 32
+  gradient_accumulation_steps: 4
+  num_epochs: 1000
+  seed: 42
+  gradient_clip: 0.01
+  ema_rate: 0.9999
+
+  optimizer:
+    lr: 2e-5
+    weight_decay: 0.01
+    betas: [0.9, 0.999]
+
+  scheduler:
+    warmup_steps: 1000
+    min_lr_ratio: 0.1
+
+  classifier_free_guidance:
+    conditioning_schedule:
+      - mask: [uni, ge]
+        weight: 16
+      - mask: [ge]
+        weight: 24
+      - mask: [uni]
+        weight: 24
+      - mask: []
+        weight: 36
+
+  modality_monitor:
+    enabled: true
+    diagnostic_freq: 10
+    diagnostic_batch_size: 64
+
+  convergence:
+    monitor_timestep_range: [900, 1000]
+    patience: 10
+    min_epochs: 50
+
+distributed:
+  precision: "bf16-mixed"
+  compile_model: true
+
+checkpoint:
+  save_every: 1000
+  resume: null
+
+logging:
+  log_every: 100
+  validate_every: 0
+  gpu_monitor: true
+  gpu_monitor_interval: 60.0
+  sample_every_epochs: 10
+  sample_every_steps: 0
+  num_samples: 16
+  sample_guidance_scale: 3.0
+  sample_num_steps: 20
+  sample_vae_path: "/cluster/home/pvlachas/leomed-home/pretrained_model_weights/stability-ai-stable-diffusion-3-5-large/models--stabilityai--stable-diffusion-3.5-large/snapshots/ceddf0a7fdf2064ea28e2213e3b84e4afa170a0f/vae"