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lucid-dl
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diamond

Reinforcement Learning
Safetensors
lucid
world-modeling
diamond
Model card Files
xet
 Community
diamond
File size: 1,758 Bytes
5765b92
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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{
  "library_name": "lucid",
  "architecture": "diamond",
  "model_type": "diamond",
  "task": "world-modeling",
  "config": {
    "sample_size": 64,
    "in_channels": 3,
    "out_channels": 3,
    "act_fn": "silu",
    "num_actions": 18,
    "conditioning_frames": 4,
    "unet_channels": [
      64,
      64,
      64,
      64
    ],
    "unet_layers": [
      2,
      2,
      2,
      2
    ],
    "cond_dim": 256,
    "sigma_data": 0.5,
    "p_mean": -0.4,
    "p_std": 1.2,
    "sigma_offset_noise": 0.3,
    "attention_head_dim": 8,
    "denoise_steps": 3,
    "reward_channels": [
      32,
      32,
      32,
      32
    ],
    "reward_layers": [
      2,
      2,
      2,
      2
    ],
    "reward_cond_dim": 128,
    "reward_frames": 2,
    "reward_lstm_dim": 512,
    "actor_channels": [
      32,
      32,
      64,
      64
    ],
    "actor_layers": [
      1,
      1,
      1,
      1
    ],
    "actor_lstm_dim": 512,
    "horizon": 15,
    "gamma": 0.985,
    "lambda_": 0.95,
    "entropy_weight": 0.001,
    "burn_in": 4
  },
  "preprocessing": {
    "resize": 64,
    "rescale": 0.00784313725490196,
    "mean": [
      0.5,
      0.5,
      0.5
    ],
    "std": [
      0.5,
      0.5,
      0.5
    ]
  },
  "weights": {
    "tag": "Boxing",
    "num_classes": 18,
    "license": "mit",
    "source": "https://huggingface.co/eloialonso/diamond",
    "num_params": 0,
    "game": "Boxing",
    "num_actions": 18,
    "denoising_steps": 3,
    "sha256": "94979c2f4d10bd6ef41340d9b49ec43b80ebbac93bb8b9ac1722578495086c8d",
    "file_size_mb": 51.72
  },
  "id2label": {
    "0": "generative",
    "1": "diffusion",
    "2": "world-model"
  },
  "label2id": {
    "generative": 0,
    "diffusion": 1,
    "world-model": 2
  }
}