CUDA error: no kernel image is available for execution on the device

e.
/usr/local/lib/python3.10/dist-packages/torch/cuda/__init__.py:235: UserWarning:
NVIDIA GeForce RTX 5090 with CUDA capability sm_120 is not compatible with the current PyTorch installation.
The current PyTorch install supports CUDA capabilities sm_50 sm_60 sm_70 sm_75 sm_80 sm_86 sm_90.
If you want to use the NVIDIA GeForce RTX 5090 GPU with PyTorch, please check the instructions at https://pytorch.org/get-started/locally/

warnings.warn(
模型加载失败: CUDA error: no kernel image is available for execution on the device
CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1
Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.

Traceback (most recent call last):
File "/app/start_ocr_webui.py", line 76, in load_model
self.model = self.model.eval().cuda().to(torch.bfloat16)
File "/usr/local/lib/python3.10/dist-packages/transformers/modeling_utils.py", line 3157, in to
return super().to(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1343, in to
return self._apply(convert)
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 903, in _apply
module._apply(fn)
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 903, in _apply
module._apply(fn)
模型加载失败: CUDA error: no kernel image is available for execution on the device
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 930, in _apply
param_applied = fn(param)
CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1329, in convert
Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.
return t.to(

RuntimeError: CUDA error: no kernel image is available for execution on the device
CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1
Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.
这是什么问题