Stable Diffusion "A tensor with all NaNs was produced in Unet" hatası

 Error completing request
*** Arguments: ('task(7sxhraoabro66lc)', 'apple', '', [], 20, 0, False, False, 1, 1, 7, -1.0, -1.0, 0, 0, 0, False, 512, 512, False, 0.7, 2, 'Latent', 0, 0, 0, 0, '', '', [], 0, False, False, 'positive', 'comma', 0, False, False, '', 1, '', [], 0, '', [], 0, '', [], True, False, False, False, 0) {}
    Traceback (most recent call last):
      File "C:\Users\kkert\OneDrive\Masaüstü\stable-diffusion-webui\modules\call_queue.py", line 55, in f
        res = list(func(*args, **kwargs))
      File "C:\Users\kkert\OneDrive\Masaüstü\stable-diffusion-webui\modules\call_queue.py", line 35, in f
        res = func(*args, **kwargs)
      File "C:\Users\kkert\OneDrive\Masaüstü\stable-diffusion-webui\modules\txt2img.py", line 57, in txt2img
        processed = processing.process_images(p)
      File "C:\Users\kkert\OneDrive\Masaüstü\stable-diffusion-webui\modules\processing.py", line 620, in process_images
        res = process_images_inner(p)
      File "C:\Users\kkert\OneDrive\Masaüstü\stable-diffusion-webui\modules\processing.py", line 739, in process_images_inner
        samples_ddim = p.sample(conditioning=p.c, unconditional_conditioning=p.uc, seeds=p.seeds, subseeds=p.subseeds, subseed_strength=p.subseed_strength, prompts=p.prompts)
      File "C:\Users\kkert\OneDrive\Masaüstü\stable-diffusion-webui\modules\processing.py", line 992, in sample
        samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
      File "C:\Users\kkert\OneDrive\Masaüstü\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 439, in sample
        samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args={
      File "C:\Users\kkert\OneDrive\Masaüstü\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 278, in launch_sampling
        return func()
      File "C:\Users\kkert\OneDrive\Masaüstü\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 439, in <lambda>
        samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args={
      File "C:\Users\kkert\OneDrive\Masaüstü\stable-diffusion-webui\venv\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
        return func(*args, **kwargs)
      File "C:\Users\kkert\OneDrive\Masaüstü\stable-diffusion-webui\repositories\k-diffusion\k_diffusion\sampling.py", line 145, in sample_euler_ancestral
        denoised = model(x, sigmas[i] * s_in, **extra_args)
      File "C:\Users\kkert\OneDrive\Masaüstü\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "C:\Users\kkert\OneDrive\Masaüstü\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 190, in forward
        devices.test_for_nans(x_out, "unet")
      File "C:\Users\kkert\OneDrive\Masaüstü\stable-diffusion-webui\modules\devices.py", line 158, 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 setting the "Upcast cross attention layer to float32" option in Settings > Stable Diffusion or using the --no-half commandline argument to fix this. Use --disable-nan-check commandline argument to disable this check.

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