Add GEOM-Drugs epoch 100 and QM9 epochs 1000 and 1500 with inference assets

cd01066 verified 18 days ago

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# GEOM-Drugs with explicit hydrogens

Published completed epochs: 50, 100.

Continued from the best checkpoint after 48 completed epochs. The training subset contains at most 72 atoms including hydrogen.

The original Lightning checkpoints include current weights, EMA weights and optimizer state. The inference loader constructs only the selected network (EMA by default).

```python
from morph.inference import load_pretrained
model = load_pretrained("geom-explicit-h", epoch=100, device="cuda")
trajectories, validity, vocab, coordinate_std = model.generate(n_mols=16)
```

Coordinates returned by generation are in Angstrom. Config, vocabularies and training distributions are included; no dataset is needed for inference. Training settings and source are in `training_bundle.tar.gz`.

	# GEOM-Drugs with explicit hydrogens

	Published completed epochs: 50, 100.

	Continued from the best checkpoint after 48 completed epochs. The training subset contains at most 72 atoms including hydrogen.

	The original Lightning checkpoints include current weights, EMA weights and optimizer state. The inference loader constructs only the selected network (EMA by default).

	```python
	from morph.inference import load_pretrained

	model = load_pretrained("geom-explicit-h", epoch=100, device="cuda")
	trajectories, validity, vocab, coordinate_std = model.generate(n_mols=16)
	```

	Coordinates returned by generation are in Angstrom. Config, vocabularies and training distributions are included; no dataset is needed for inference. Training settings and source are in `training_bundle.tar.gz`.