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README.md

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+---
+license: mit
+library_name: pytorch-lightning
+pretty_name: MOFFlow-2 Pretrained Checkpoints
+---
+
+# MOFFlow-2 Pretrained Checkpoints
+
+Pretrained checkpoints and configs for **MOFFlow-2** tasks:
+- Structure prediction (`csp`)
+- Generation (`gen`)
+
+Project repo: https://github.com/nayoung10/MOFFlow-2
+
+## Files
+
+- `csp/config.yaml`
+- `csp/sp_module_ckpt.tar.gz`
+- `gen/sp_module/config.yaml`
+- `gen/sp_module/sp_module_ckpt.tar.gz`
+- `gen/seq_module_unconditional/config.yaml`
+- `gen/seq_module_unconditional/seq_module_unconditional_ckpt.tar.gz`
+- `gen/seq_module_conditional/config.yaml`
+- `gen/seq_module_conditional/seq_module_conditional_ckpt.tar.gz`
+- `SHA256SUMS`
+
+## Quick Start (download + verify + extract)
+
+```bash
+# Download all files from this model repo
+hf download lkny123/mofflow2-ckpt --repo-type model --local-dir .
+
+# Verify integrity
+sha256sum -c SHA256SUMS
+```
+
+Extract checkpoint archives in place:
+
+```bash
+tar -xzf csp/sp_module_ckpt.tar.gz -C csp
+tar -xzf gen/sp_module/sp_module_ckpt.tar.gz -C gen/sp_module
+tar -xzf gen/seq_module_unconditional/seq_module_unconditional_ckpt.tar.gz -C gen/seq_module_unconditional
+tar -xzf gen/seq_module_conditional/seq_module_conditional_ckpt.tar.gz -C gen/seq_module_conditional
+```
+
+## How to use with MOFFlow-2
+
+Important: `config.yaml` must be in the **same directory** as the checkpoint file used in `inference.ckpt_path`.
+
+Example:
+
+```bash
+python -m experiments.predict \
+  inference.task=csp \
+  inference.ckpt_path=<path_to_ckpt_file_inside_csp_dir>
+```
+
+For sequence generation:
+
+```bash
+python -m experiments.predict_seq \
+  inference.ckpt_path=<path_to_ckpt_file_inside_gen/seq_module_unconditional_or_conditional>
+```
+
+## Notes
+
+- Checkpoint files are PyTorch Lightning `.ckpt`.
+- Archive members may include epoch/step in filename.
+- Use the extracted checkpoint path directly in `inference.ckpt_path`.