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`LoRACompatibleConv` is deprecated and will be removed in version 1.0.0. Use of `LoRACompatibleConv` is deprecated. Please switch to PEFT backend by installing PEFT: `pip install peft`.
deprecate("LoRACompatibleConv", "1.0.0", deprecation_message)
Some weights of the model checkpoint at ./pretrained_weights/sd-image-variations-diffusers were not used when initializing UNet2DConditionModel: ['conv_out.bias', 'conv_norm_out.bias', 'conv_out.weight', 'conv_norm_out.weight']
- This IS expected if you are initializing UNet2DConditionModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing UNet2DConditionModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
The text was updated successfully, but these errors were encountered:
Width: 200
Height: 200
Length: 300
Slice: 48
Overlap: 4
Classifier free guidance: 3.5
DDIM sampling steps : 20
skip 1
ref_img_ref_video_dance_3.5_20_1.mp4
logs
The text was updated successfully, but these errors were encountered: