imaginAIry/imaginairy/configs/stable-diffusion-v2-inference.yaml
Bryce e67341223b feature: Stable Diffusion 2.0
working: CUDA and MacOS
working: 512p model with all samplers
working: inpainting with all samplers
working: 768p model with ddim sampler
2022-11-24 00:50:57 -08:00

68 lines
1.8 KiB
YAML

model:
base_learning_rate: 1.0e-4
target: imaginairy.modules.diffusion.ddpm.LatentDiffusion
params:
linear_start: 0.00085
linear_end: 0.0120
num_timesteps_cond: 1
log_every_t: 200
timesteps: 1000
first_stage_key: "jpg"
cond_stage_key: "txt"
image_size: 64
channels: 4
cond_stage_trainable: false
conditioning_key: crossattn
monitor: val/loss_simple_ema
scale_factor: 0.18215
use_ema: False # we set this to false because this is an inference only config
unet_config:
target: imaginairy.modules.diffusion.openaimodel.UNetModel
params:
use_checkpoint: True
use_fp16: False
image_size: 32 # unused
in_channels: 4
out_channels: 4
model_channels: 320
attention_resolutions: [ 4, 2, 1 ]
num_res_blocks: 2
channel_mult: [ 1, 2, 4, 4 ]
num_head_channels: 64 # need to fix for flash-attn
use_spatial_transformer: True
use_linear_in_transformer: True
transformer_depth: 1
context_dim: 1024
legacy: False
first_stage_config:
target: imaginairy.modules.autoencoder.AutoencoderKL
params:
embed_dim: 4
monitor: val/rec_loss
ddconfig:
#attn_type: "vanilla-xformers"
double_z: true
z_channels: 4
resolution: 256
in_channels: 3
out_ch: 3
ch: 128
ch_mult:
- 1
- 2
- 4
- 4
num_res_blocks: 2
attn_resolutions: []
dropout: 0.0
lossconfig:
target: torch.nn.Identity
cond_stage_config:
target: imaginairy.modules.encoders.FrozenOpenCLIPEmbedder
params:
freeze: True
layer: "penultimate"