CUDA out of memory

При попытке запуститься говорит о нехватке памяти видеокарты RTX 3050ti.
When trying to start, it indicates a lack of memory of the RTX 3050ti video card.

`◼️ Malevich is 1.3 billion params model from the family GPT3-like, that uses Russian language and text+image multi-modality.
x4 --> ready
tokenizer --> ready
Working with z of shape (1, 256, 32, 32) = 262144 dimensions.
vae --> ready
ruclip --> ready
Traceback (most recent call last):
File ".\Text Document.py", line 12, in
ruclip = ruclip.to(device)
File "C:\Users\bropi\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.8_qbz5n2kfra8p0\LocalCache\local-packages\Python38\site-packages\torch\nn\modules\module.py", line 899, in to
return self._apply(convert)
File "C:\Users\bropi\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.8_qbz5n2kfra8p0\LocalCache\local-packages\Python38\site-packages\torch\nn\modules\module.py", line 570, in _apply
module._apply(fn)
File "C:\Users\bropi\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.8_qbz5n2kfra8p0\LocalCache\local-packages\Python38\site-packages\torch\nn\modules\module.py", line 570, in _apply
module._apply(fn)
File "C:\Users\bropi\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.8_qbz5n2kfra8p0\LocalCache\local-packages\Python38\site-packages\torch\nn\modules\module.py", line 570, in _apply
module._apply(fn)
[Previous line repeated 3 more times]
File "C:\Users\bropi\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.8_qbz5n2kfra8p0\LocalCache\local-packages\Python38\site-packages\torch\nn\modules\module.py", line 593, in _apply
param_applied = fn(param)
File "C:\Users\bropi\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.8_qbz5n2kfra8p0\LocalCache\local-packages\Python38\site-packages\torch\nn\modules\module.py", line 897, in convert
return t.to(device, dtype if t.is_floating_point() or t.is_complex() else None, non_blocking)
RuntimeError: CUDA out of memory. Tried to allocate 2.00 MiB (GPU 0; 4.00 GiB total capacity; 2.86 GiB already allocated; 0 bytes free; 2.93 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF`