DIAMOND (CSGO)

https://arxiv.org/abs/2405.12399

Lucid port of https://huggingface.co/eloialonso/diamond, converted to Lucid-native safetensors.

Available weights

Tag	Params	GFLOPs	Size	Source
Alien (default)	0.0M	—	51.72 MB	eloialonso/diamond
Amidar	0.0M	—	51.7 MB	eloialonso/diamond
Assault	0.0M	—	51.69 MB	eloialonso/diamond
Asterix	0.0M	—	51.69 MB	eloialonso/diamond
BankHeist	0.0M	—	51.72 MB	eloialonso/diamond
BattleZone	0.0M	—	51.72 MB	eloialonso/diamond
Boxing	0.0M	—	51.72 MB	eloialonso/diamond
Breakout	0.0M	—	51.68 MB	eloialonso/diamond
CSGO	0.0M	—	1455.92 MB	eloialonso/diamond
ChopperCommand	0.0M	—	51.72 MB	eloialonso/diamond
CrazyClimber	0.0M	—	51.69 MB	eloialonso/diamond
DemonAttack	0.0M	—	51.69 MB	eloialonso/diamond
Freeway	0.0M	—	51.68 MB	eloialonso/diamond
Frostbite	0.0M	—	51.72 MB	eloialonso/diamond
Gopher	0.0M	—	51.69 MB	eloialonso/diamond
Hero	0.0M	—	51.72 MB	eloialonso/diamond
Jamesbond	0.0M	—	51.72 MB	eloialonso/diamond
Kangaroo	0.0M	—	51.72 MB	eloialonso/diamond
Krull	0.0M	—	51.72 MB	eloialonso/diamond
KungFuMaster	0.0M	—	51.71 MB	eloialonso/diamond
MsPacman	0.0M	—	51.69 MB	eloialonso/diamond
Pong	0.0M	—	51.69 MB	eloialonso/diamond
PrivateEye	0.0M	—	51.72 MB	eloialonso/diamond
Qbert	0.0M	—	51.69 MB	eloialonso/diamond
RoadRunner	0.0M	—	51.72 MB	eloialonso/diamond
Seaquest	0.0M	—	51.72 MB	eloialonso/diamond
UpNDown	0.0M	—	51.69 MB	eloialonso/diamond

Usage

import lucid.models as models
from lucid.models.weights import DiamondWeights

# default tag
model = models.diamond_csgo(pretrained=True)

# explicit tag (enum or string)
model = models.diamond_csgo(weights=DiamondWeights.CSGO)
model = models.diamond_csgo(pretrained="CSGO")

# preprocessing travels with the weights
weights = DiamondWeights.CSGO
preprocess = weights.transforms()
out = model(preprocess(image)[None])
logits = out.logits  # (B, num_classes)

Conversion

Converted from https://huggingface.co/eloialonso/diamond via python -m tools.convert_weights diamond --tag CSGO. Key mapping + numerical parity verified against the source.

License

mit — inherited from the original weights.

Citation

@inproceedings{alonso2024diffusion,
  title={Diffusion for World Modeling: Visual Details Matter in Atari},
  author={Alonso, Eloi and Jelley, Adam and Micheli, Vincent and Kanervisto, Anssi and Storkey, Amos and Pearce, Tim and Fleuret, Fran{\c{c}}ois},
  booktitle={Advances in Neural Information Processing Systems (NeurIPS)},
  year={2024}
}