unet/config.json

{
 "_class_name": "UNet2DModel",
 "_diffusers_version": "0.31.0.dev0",
 "_name_or_path": "/home/yagor/\u0420\u0430\u0431\u043e\u0447\u0438\u0439 \u0441\u0442\u043e\u043b/biometric hands gen hack/uncond-image-generation-ldm/ddpm_ema_palm_512/unet",
 "act_fn": "silu",
 "add_attention": true,
 "attention_head_dim": 8,
 "attn_norm_num_groups": null,
 "block_out_channels": [
 224,
 448,
 672,
 896
 ],
 "center_input_sample": false,
 "class_embed_type": null,
 "down_block_types": [
 "DownBlock2D",
 "AttnDownBlock2D",
 "AttnDownBlock2D",
 "AttnDownBlock2D"
 ],
 "downsample_padding": 1,
 "downsample_type": "conv",
 "dropout": 0.0,
 "flip_sin_to_cos": true,
 "freq_shift": 0,
 "in_channels": 3,
 "layers_per_block": 2,
 "mid_block_scale_factor": 1,
 "norm_eps": 1e-05,
 "norm_num_groups": 32,
 "num_class_embeds": null,
 "num_train_timesteps": null,
 "out_channels": 3,
 "resnet_time_scale_shift": "default",
 "sample_size": 128,
 "time_embedding_type": "positional",
 "up_block_types": [
 "AttnUpBlock2D",
 "AttnUpBlock2D",
 "AttnUpBlock2D",
 "UpBlock2D"
 ],
 "upsample_type": "conv"
}