acascanzal

/

diffModel

like 0

• "transformers.models.clip.modeling_clip.CLIPMLP",
• "peft.utils.peft_types.PeftType",
• "transformers.models.clip.modeling_clip.CLIPAttention",
• "numpy.ndarray",
• "diffusers.models.unets.unet_2d_blocks.UNetMidBlock2DCrossAttn",
• "torch.nn.modules.container.ModuleList",
• "transformers.models.clip.modeling_clip.CLIPTextModel",
• "diffusers.models.attention_processor.AttnProcessor2_0",
• "numpy._core.multiarray._reconstruct",
• "diffusers.models.unets.unet_2d_blocks.UpDecoderBlock2D",
• "collections.defaultdict",
• "diffusers.models.unets.unet_2d_blocks.UNetMidBlock2D",
• "torch.nn.modules.normalization.LayerNorm",
• "transformers.activations.QuickGELUActivation",
• "tokenizers.Tokenizer",
• "__builtin__.list",
• "diffusers.models.unets.unet_2d_condition.UNet2DConditionModel",
• "diffusers.schedulers.scheduling_pndm.PNDMScheduler",
• "torch.FloatStorage",
• "torch.HalfStorage",
• "torch.nn.modules.sparse.Embedding",
• "diffusers.models.resnet.ResnetBlock2D",
• "__builtin__.set",
• "torch.nn.modules.container.ParameterDict",
• "transformers.models.clip.modeling_clip.CLIPTextEmbeddings",
• "diffusers.models.downsampling.Downsample2D",
• "transformers.models.clip.modeling_clip.CLIPEncoder",
• "diffusers.models.embeddings.Timesteps",
• "torch.nn.modules.conv.Conv2d",
• "tokenizers.models.Model",
• "torch.LongStorage",
• "diffusers.models.unets.unet_2d_blocks.DownEncoderBlock2D",
• "diffusers.image_processor.VaeImageProcessor",
• "torch.nn.modules.dropout.Dropout",
• "torch._utils._rebuild_tensor_v2",
• "diffusers.models.attention_processor.Attention",
• "__builtin__.bytes",
• "diffusers.models.autoencoders.autoencoder_kl.AutoencoderKL",
• "torch.nn.modules.normalization.GroupNorm",
• "diffusers.models.transformers.transformer_2d.Transformer2DModel",
• "transformers.models.clip.tokenization_clip.CLIPTokenizer",
• "diffusers.models.upsampling.Upsample2D",
• "torch._utils._rebuild_parameter_with_state",
• "transformers.models.clip.image_processing_clip.CLIPImageProcessor",
• "peft.tuners.lora.config.LoraConfig",
• "diffusers.models.unets.unet_2d_blocks.UpBlock2D",
• "transformers.image_utils.SizeDict",
• "_codecs.encode",
• "collections.OrderedDict",
• "diffusers.models.unets.unet_2d_blocks.CrossAttnUpBlock2D",
• "diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline",
• "diffusers.models.embeddings.TimestepEmbedding",
• "torch.nn.modules.linear.Identity",
• "diffusers.models.unets.unet_2d_blocks.DownBlock2D",
• "torch.nn.modules.container.ModuleDict",
• "re._compile",
• "peft.tuners.lora.layer.Linear",
• "diffusers.models.attention_processor.SlicedAttnProcessor",
• "diffusers.models.autoencoders.vae.Encoder",
• "torch._utils._rebuild_parameter",
• "diffusers.models.activations.GEGLU",
• "peft.tuners.lora.config.LoraRuntimeConfig",
• "transformers.models.clip.configuration_clip.CLIPTextConfig",
• "torch.nn.modules.activation.SiLU",
• "transformers.core_model_loading.WeightRenaming",
• "diffusers.models.unets.unet_2d_blocks.CrossAttnDownBlock2D",
• "diffusers.models.autoencoders.vae.Decoder",
• "diffusers.models.attention.BasicTransformerBlock",
• "numpy.dtype",
• "torch.nn.modules.linear.Linear",
• "transformers.models.clip.modeling_clip.CLIPTextTransformer",
• "diffusers.models.attention.FeedForward",
• "diffusers.configuration_utils.FrozenDict",
• "transformers.models.clip.modeling_clip.CLIPEncoderLayer",
• "tokenizers.AddedToken"

How to fix it?