Unique3D / gradio_app /custom_models /image2mvimage.yaml
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pretrained_model_name_or_path: "./ckpt/img2mvimg"
mixed_precision: "bf16"
init_config:
# enable controls
enable_cross_attn_lora: False
enable_cross_attn_ip: False
enable_self_attn_lora: False
enable_self_attn_ref: False
enable_multiview_attn: True
# for cross attention
init_cross_attn_lora: False
init_cross_attn_ip: False
cross_attn_lora_rank: 256 # 0 for not enabled
cross_attn_lora_only_kv: False
ipadapter_pretrained_name: "h94/IP-Adapter"
ipadapter_subfolder_name: "models"
ipadapter_weight_name: "ip-adapter_sd15.safetensors"
ipadapter_effect_on: "all" # all, first
# for self attention
init_self_attn_lora: False
self_attn_lora_rank: 256
self_attn_lora_only_kv: False
# for self attention ref
init_self_attn_ref: False
self_attn_ref_position: "attn1"
self_attn_ref_other_model_name: "lambdalabs/sd-image-variations-diffusers"
self_attn_ref_pixel_wise_crosspond: False
self_attn_ref_effect_on: "all"
# for multiview attention
init_multiview_attn: True
multiview_attn_position: "attn1"
use_mv_joint_attn: True
num_modalities: 1
# for unet
init_unet_path: "${pretrained_model_name_or_path}"
cat_condition: True # cat condition to input
# for cls embedding
init_num_cls_label: 8 # for initialize
cls_labels: [0, 1, 2, 3] # for current task
trainers:
- trainer_type: "image2mvimage_trainer"
trainer:
pretrained_model_name_or_path: "${pretrained_model_name_or_path}"
attn_config:
cls_labels: [0, 1, 2, 3] # for current task
enable_cross_attn_lora: False
enable_cross_attn_ip: False
enable_self_attn_lora: False
enable_self_attn_ref: False
enable_multiview_attn: True
resolution: "256"
condition_image_resolution: "256"
normal_cls_offset: 4
condition_image_column_name: "conditioning_image"
image_column_name: "image"