getting this error every time i try to use the colab to train an embedding as soon as it tries to generate an image?

[riade3788]

Traceback (most recent call last):
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/textual_inversion/textual_inversion.py", line 559, in train_embedding
processed = processing.process_images(p)
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/processing.py", line 476, in process_images
res = process_images_inner(p)
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/processing.py", line 614, in process_images_inner
samples_ddim = p.sample(conditioning=c, unconditional_conditioning=uc, seeds=seeds, subseeds=subseeds, subseed_strength=p.subseed_strength, prompts=prompts)
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/processing.py", line 809, in sample
samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_samplers.py", line 544, in sample
samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args={
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_samplers.py", line 447, in launch_sampling
return func()
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_samplers.py", line 544, in
samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args={
File "/usr/local/lib/python3.8/dist-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
return func(*args, **kwargs)
File "/content/gdrive/MyDrive/sd/stablediffusion/src/k-diffusion/k_diffusion/sampling.py", line 145, in sample_euler_ancestral
denoised = model(x, sigmas[i] * s_in, **extra_args)
File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_samplers.py", line 354, in forward
devices.test_for_nans(x_out, "unet")
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/devices.py", line 136, in test_for_nans
raise NansException(message)
modules.devices.NansException: A tensor with all NaNs was produced in Unet. This could be either because there's not enough precision to represent the picture, or because your video card does not support half type. Try using --no-half commandline argument to fix this.

Applying xformers cross attention optimization.

EDIT2: everything seems to work fine on the 512 model so?!