Configuration Templates¶

Ready-to-use template configs live in the repository under docs/cfg_examples/. Copy the relevant file, fill in your checkpoint and data paths, and run it. The full packaged Hydra defaults these templates build on are under src/MolecularDiffusion/configs/.

Training¶

Template	Purpose
`docs/cfg_examples/train_diffusion.yaml`	Train an EDM diffusion model from scratch.
`docs/cfg_examples/finetune_diffusion.yaml`	Fine-tune from a pretrained diffusion checkpoint.
`docs/cfg_examples/train_regressor.yaml`	Train a property regressor.
`docs/cfg_examples/train_guidance.yaml`	Train a guidance (property) model.

MolCraftDiff train docs/cfg_examples/train_diffusion

Generation¶

Template	Mode (`interference.task_type`)
`docs/cfg_examples/gen_unconditional.yaml`	`unconditional`
`docs/cfg_examples/gen_cfg.yaml`	`cfg` — classifier-free guidance
`docs/cfg_examples/gen_gradient_guidance.yaml`	`gg` — gradient guidance
`docs/cfg_examples/gen_hybrid_cfg_gg.yaml`	`cfggg` — hybrid CFG + GG
`docs/cfg_examples/gen_inpaint.yaml`	`inpaint` — structure inpainting
`docs/cfg_examples/gen_outpaint.yaml`	`outpaint` — fragment extension

MolCraftDiff generate docs/cfg_examples/gen_cfg

Every command accepts Hydra-style dotted overrides, e.g. MolCraftDiff generate docs/cfg_examples/gen_cfg interference.num_generate=200. See Model Architectures for choosing a training backbone and Tutorials for end-to-end walkthroughs.