Create README.md

README.md

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+下面是完整 Markdown，可直接复制到 HF README：
+
+````markdown
+---
+base_model:
+- lambda/miniSD-diffusers
+- stabilityai/stable-diffusion-3-medium-diffusers
+license: apache-2.0
+---
+
+# Causal-Adapter Pretrained Weights
+
+## Model Overview
+
+This repository provides pretrained Causal-Adapter weights across four benchmark settings. The released checkpoints include Causal-Adapter models built on both SD1.5-style and SD3-style diffusion structures.
+
+Causal-Adapter is designed to inject structured causal semantics into pretrained text-to-image diffusion models for controllable and causally consistent counterfactual image generation.
+
+Detailed usage examples are available in our notebook benchmarks:
+
+[Notebook Benchmarks](https://github.com/LeiTong02/Causal-Adapter/tree/main/notebook_benchmarks)
+
+An example configuration can be found in:
+
+```text
+notebook_benchmarks/counterfactuals_celeba.ipynb
+````
+
+## Base Models
+
+The released checkpoints are based on the following pretrained diffusion backbones:
+
+* **SD1.5-style structure:** `lambda/miniSD-diffusers`
+* **SD3-style structure:** `stabilityai/stable-diffusion-3-medium-diffusers`
+
+## Benchmark Resources
+
+* **Pendulum dataset generation:**
+  [CausalVAE Pendulum](https://github.com/huawei-noah/trustworthyAI/blob/master/research/CausalVAE/causal_data/pendulum.py)
+
+* **CelebA and ADNI benchmark configuration:**
+  [counterfactual-benchmark](https://github.com/gulnazaki/counterfactual-benchmark)
+
+* **CelebA-HQ dataset:**
+  [CelebAMask-HQ](https://github.com/switchablenorms/CelebAMask-HQ)
+
+## Example Configuration
+
+The following example shows the main paths required for running the CelebA counterfactual generation notebook.
+
+```python
+import os
+
+# Shared roots
+
+# 1) Frozen SD1.5 backbone.
+# For example: "lambda/miniSD-diffusers"
+BASE_MODEL_PATH = ""
+
+# 2) Causal-Adapter ControlNet checkpoint and the matching MCPL learned pseudo-tokens.
+# Example ControlNet checkpoint:
+# https://huggingface.co/LeiTong/Causal-Adapter/tree/main/celeba/controlnet/controlnet-steps-200000.safetensors
+CONTROLNET_PATH = ""
+
+# Example learned text embeddings:
+# https://huggingface.co/LeiTong/Causal-Adapter/tree/main/celeba/controlnet/learned_embeds-steps-200000.safetensors
+TEXT_EMBEDDING_PATH = ""
+
+# 3) Optional pretrained SCM head from SCM_modeling/.
+# Example SCM checkpoint:
+# https://huggingface.co/LeiTong/Causal-Adapter/tree/main/celeba/scm/best_model.pt
+SCM_PATH = ""
+
+# 4) CelebA root expected by torchvision.datasets.CelebA(root=...).
+DATA_ROOT = os.environ.get("DATA_ROOT", "")
+
+DATASET = "celeA_complex"
+SIZE = 256
+```
+
+## License
+
+This repository is released under the Apache-2.0 license.
+
+```
+```