Hi, I’m new to using HuggingFace.

I try to set up the model UNet1DModel and I can’t get output working:

from diffusers import UNet1DModel

batch_size, sample_size, num_channels = 1, 128, 1

model = UNet1DModel(

sample_size=sample_size,

in_channels=num_channels,

out_channels=num_channels,

)

#
sample (`torch.FloatTensor`

): `(batch_size, sample_size, num_channels)`

noisy inputs tensor

sample = torch.randn(batch_size, sample_size, num_channels)

timestep = torch.zeros(batch_size, dtype=torch.int)

output = model(sample, timestep)

it gives me:

/usr/local/lib/python3.7/dist-packages/torch/nn/modules/conv.py in _conv_forward(self, input, weight, bias) 302 _single(0), self.dilation, self.groups) 303 return F.conv1d(input, weight, bias, self.stride, → 304 self.padding, self.dilation, self.groups) 305 306 def forward(self, input: Tensor) → Tensor:

RuntimeError: Given groups=1, weight of size [32, 1, 1], expected input[1, 144, 1] to have 1 channels, but got 144 channels instead

any help is appreciated

thanks