Initial release: BoYueGRN model checkpoints and model card

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README.md

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+---
+license: apache-2.0
+tags:
+  - genomics
+  - single-cell
+  - gene-regulatory-network
+  - causal-discovery
+  - graph-transformer
+---
+# BoYueGRN model checkpoints
+
+Model weights for **BoYueGRN**, an amortized causal-discovery framework that
+infers directed gene regulatory networks (GRNs) from single-cell RNA-seq.
+BoYueGRN is trained exclusively on 10,000 synthetic structural causal models;
+a single forward pass infers both edge probabilities and regulatory directions
+for any new dataset, and TF-centric sliding windows with asymmetric fusion
+extend the fixed-size model to whole-transcriptome coverage.
+
+**About the name.** "BoYue" (博约, *bó yuē*) is taken from Su Shi's (苏轼,
+Song dynasty) "博观而约取，厚积而薄发" — "observe broadly and take precisely,
+accumulate richly and release sparingly": the model observes a broad ensemble
+of synthetic SCMs offline, then amortizes that cost into a single forward pass
+on any new dataset.
+
+Companion code repository (GitHub): **https://github.com/holaoctopus/BoYueGRN**
+(pip-installable `boyue` package + full training / benchmark / case-study
+pipeline).
+
+***
+
+## Contents
+
+```
+checkpoints/
+├── main/                          # production models (paper results)
+│   ├── edge_v3_seed{0,1,2,3}.pt                    # edge existence, 4-seed ensemble
+│   ├── dir_specialist_tf_non_tf_seed{0,1,2,3}.pt   # NT direction specialist (TF→non-TF)
+│   └── dir_specialist_tf_tf_seed0.pt               # TT direction specialist (TF→TF)
+└── ablation/                      # 7 ablation models (Table 2)
+    ├── edge_v3_20k_seed0.pt
+    ├── edge_g300_seed0.pt
+    ├── edge_rdrop_seed0.pt
+    ├── dir_weighted_w3_seed0.pt
+    ├── dir_lowrank_r64_seed0.pt
+    ├── dir_attn_seed0.pt
+    └── joint_lambda03_seed0.pt
+```
+
+- `main/` ≈ 896 MB (9 files)
+- `ablation/` ≈ 699 MB (7 files)
+- **total ≈ 1.6 GB (16 files)**
+
+Each checkpoint is a `torch` `state_dict` dict:
+
+- edge models → `{'encoder', 'edge_head'}`
+- direction models → `{'encoder', 'dir_head'}`
+- joint model → `{'encoder', 'edge_head', 'dir_head', 'lambda_dir'}`
+
+## Loading
+
+Install the companion package, then point `load_ensemble` at these files:
+
+```bash
+pip install -e /path/to/BoYueGRN   # the GitHub repo (boyue package)
+```
+
+```python
+import torch
+from boyue import load_ensemble
+
+inf = load_ensemble(
+    edge_ckpts=['checkpoints/main/edge_v3_seed0.pt'],
+    dir_ckpts=['checkpoints/main/dir_specialist_tf_non_tf_seed0.pt'],
+    device=torch.device('cpu'),    # or torch.device('cuda')
+)
+```
+
+Quick sanity check on a random 200×200 expression matrix:
+
+```python
+import numpy as np
+X = np.random.gamma(2.0, 1.0, (200, 200)).astype(np.float32)
+out = inf.predict_from_expression(X)
+print(out.keys())   # {'edge_p', 'dir_p', ...}
+```
+
+## Downloading
+
+```python
+from huggingface_hub import snapshot_download
+snapshot_download(repo_id="Holaoctopus/boyuegrn", repo_type="model",
+                  local_dir="./boyuegrn_ckpt")
+```
+
+## License
+
+- **Code** (`boyue/` and pipeline scripts in the GitHub repo): Apache License 2.0.
+- **Weights** in this repository: Apache License 2.0 (see `LICENSE`).

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