How can I fix this Error?

[zzz12330]

Can someone help me?
Thanks !
[Dataset 0]
loading image sizes.
100%|██████████████████████████████████████████████████████████████████████████████████| 76/76 [00:01<00:00, 38.18it/s]
prepare dataset
preparing accelerator
Using accelerator 0.15.0 or above.
loading model for process 0/1
load StableDiffusion checkpoint: D:/stable diffusion/stable-diffusion-webui/models/Stable-diffusion/v1-5-pruned.safetensors
loading u-net:
loading vae:
Downloading pytorch_model.bin: 1%|▎ | 10.5M/1.71G [00:20<25:27, 1.11MB/s]╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮
│ D:\kohya_ss\venv\lib\site-packages\urllib3\response.py:444 in _error_catcher │
│ │
│ 441 │ │ │
│ 442 │ │ try: │
│ 443 │ │ │ try: │
│ ❱ 444 │ │ │ │ yield │
│ 445 │ │ │ │
│ 446 │ │ │ except SocketTimeout: │
│ 447 │ │ │ │ # FIXME: Ideally we'd like to include the url in the ReadTimeoutError bu │
│ │
│ D:\kohya_ss\venv\lib\site-packages\urllib3\response.py:567 in read │
│ │
│ 564 │ │ fp_closed = getattr(self._fp, "closed", False) │
│ 565 │ │ │
│ 566 │ │ with self._error_catcher(): │
│ ❱ 567 │ │ │ data = self._fp_read(amt) if not fp_closed else b"" │
│ 568 │ │ │ if amt is None: │
│ 569 │ │ │ │ flush_decoder = True │
│ 570 │ │ │ else: │
│ │
│ D:\kohya_ss\venv\lib\site-packages\urllib3\response.py:533 in _fp_read │
│ │
│ 530 │ │ │ return buffer.getvalue() │
│ 531 │ │ else: │
│ 532 │ │ │ # StringIO doesn't like amt=None │
│ ❱ 533 │ │ │ return self._fp.read(amt) if amt is not None else self._fp.read() │
│ 534 │ │
│ 535 │ def read(self, amt=None, decode_content=None, cache_content=False): │
│ 536 │ │ """ │
│ │
│ C:\Users\qqq99\AppData\Local\Programs\Python\Python310\lib\http\client.py:465 in read │
│ │
│ 462 │ │ │ if self.length is not None and amt > self.length: │
│ 463 │ │ │ │ # clip the read to the "end of response" │
│ 464 │ │ │ │ amt = self.length │
│ ❱ 465 │ │ │ s = self.fp.read(amt) │
│ 466 │ │ │ if not s and amt: │
│ 467 │ │ │ │ # Ideally, we would raise IncompleteRead if the content-length │
│ 468 │ │ │ │ # wasn't satisfied, but it might break compatibility. │
│ │
│ C:\Users\qqq99\AppData\Local\Programs\Python\Python310\lib\socket.py:705 in readinto │
│ │
│ 702 │ │ │ raise OSError("cannot read from timed out object") │
│ 703 │ │ while True: │
│ 704 │ │ │ try: │
│ ❱ 705 │ │ │ │ return self._sock.recv_into(b) │
│ 706 │ │ │ except timeout: │
│ 707 │ │ │ │ self._timeout_occurred = True │
│ 708 │ │ │ │ raise │
│ │
│ C:\Users\qqq99\AppData\Local\Programs\Python\Python310\lib\ssl.py:1274 in recv_into │
│ │
│ 1271 │ │ │ │ raise ValueError( │
│ 1272 │ │ │ │ "non-zero flags not allowed in calls to recv_into() on %s" % │
│ 1273 │ │ │ │ self.class) │
│ ❱ 1274 │ │ │ return self.read(nbytes, buffer) │
│ 1275 │ │ else: │
│ 1276 │ │ │ return super().recv_into(buffer, nbytes, flags) │
│ 1277 │
│ │
│ C:\Users\qqq99\AppData\Local\Programs\Python\Python310\lib\ssl.py:1130 in read │
│ │
│ 1127 │ │ │ raise ValueError("Read on closed or unwrapped SSL socket.") │
│ 1128 │ │ try: │
│ 1129 │ │ │ if buffer is not None: │
│ ❱ 1130 │ │ │ │ return self._sslobj.read(len, buffer) │
│ 1131 │ │ │ else: │
│ 1132 │ │ │ │ return self._sslobj.read(len) │
│ 1133 │ │ except SSLError as x: │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
TimeoutError: The read operation timed out

During handling of the above exception, another exception occurred:

╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮
│ D:\kohya_ss\venv\lib\site-packages\requests\models.py:816 in generate │
│ │
│ 813 │ │ │ # Special case for urllib3. │
│ 814 │ │ │ if hasattr(self.raw, "stream"): │
│ 815 │ │ │ │ try: │
│ ❱ 816 │ │ │ │ │ yield from self.raw.stream(chunk_size, decode_content=True) │
│ 817 │ │ │ │ except ProtocolError as e: │
│ 818 │ │ │ │ │ raise ChunkedEncodingError(e) │
│ 819 │ │ │ │ except DecodeError as e: │
│ │
│ D:\kohya_ss\venv\lib\site-packages\urllib3\response.py:628 in stream │
│ │
│ 625 │ │ │ │ yield line │
│ 626 │ │ else: │
│ 627 │ │ │ while not is_fp_closed(self._fp): │
│ ❱ 628 │ │ │ │ data = self.read(amt=amt, decode_content=decode_content) │
│ 629 │ │ │ │ │
│ 630 │ │ │ │ if data: │
│ 631 │ │ │ │ │ yield data │
│ │
│ D:\kohya_ss\venv\lib\site-packages\urllib3\response.py:566 in read │
│ │
│ 563 │ │ flush_decoder = False │
│ 564 │ │ fp_closed = getattr(self._fp, "closed", False) │
│ 565 │ │ │
│ ❱ 566 │ │ with self._error_catcher(): │
│ 567 │ │ │ data = self._fp_read(amt) if not fp_closed else b"" │
│ 568 │ │ │ if amt is None: │
│ 569 │ │ │ │ flush_decoder = True │
│ │
│ C:\Users\qqq99\AppData\Local\Programs\Python\Python310\lib\contextlib.py:153 in exit │
│ │
│ 150 │ │ │ │ # tell if we get the same exception back │
│ 151 │ │ │ │ value = typ() │
│ 152 │ │ │ try: │
│ ❱ 153 │ │ │ │ self.gen.throw(typ, value, traceback) │
│ 154 │ │ │ except StopIteration as exc: │
│ 155 │ │ │ │ # Suppress StopIteration unless it's the same exception that │
│ 156 │ │ │ │ # was passed to throw(). This prevents a StopIteration │
│ │
│ D:\kohya_ss\venv\lib\site-packages\urllib3\response.py:449 in _error_catcher │
│ │
│ 446 │ │ │ except SocketTimeout: │
│ 447 │ │ │ │ # FIXME: Ideally we'd like to include the url in the ReadTimeoutError bu │
│ 448 │ │ │ │ # there is yet no clean way to get at it from this context. │
│ ❱ 449 │ │ │ │ raise ReadTimeoutError(self._pool, None, "Read timed out.") │
│ 450 │ │ │ │
│ 451 │ │ │ except BaseSSLError as e: │
│ 452 │ │ │ │ # FIXME: Is there a better way to differentiate between SSLErrors? │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
ReadTimeoutError: HTTPSConnectionPool(host='cdn-lfs.huggingface.co', port=443): Read timed out.

During handling of the above exception, another exception occurred:

╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮
│ D:\kohya_ss\train_network.py:864 in │
│ │
│ 861 │ args = parser.parse_args() │
│ 862 │ args = train_util.read_config_from_file(args, parser) │
│ 863 │ │
│ ❱ 864 │ train(args) │
│ 865 │
│ │
│ D:\kohya_ss\train_network.py:160 in train │
│ │
│ 157 │ weight_dtype, save_dtype = train_util.prepare_dtype(args) │
│ 158 │ │
│ 159 │ # モデルを読み込む │
│ ❱ 160 │ text_encoder, vae, unet, _ = train_util.load_target_model(args, weight_dtype, accele │
│ 161 │ │
│ 162 │ # モデルに xformers とか memory efficient attention を組み込む │
│ 163 │ train_util.replace_unet_modules(unet, args.mem_eff_attn, args.xformers) │
│ │
│ D:\kohya_ss\library\train_util.py:3061 in load_target_model │
│ │
│ 3058 │ │ if pi == accelerator.state.local_process_index: │
│ 3059 │ │ │ print(f"loading model for process {accelerator.state.local_process_index}/{a │
│ 3060 │ │ │ │
│ ❱ 3061 │ │ │ text_encoder, vae, unet, load_stable_diffusion_format = _load_target_model( │
│ 3062 │ │ │ │ args, weight_dtype, accelerator.device if args.lowram else "cpu" │
│ 3063 │ │ │ ) │
│ 3064 │
│ │
│ D:\kohya_ss\library\train_util.py:3027 in _load_target_model │
│ │
│ 3024 │ load_stable_diffusion_format = os.path.isfile(name_or_path) # determine SD or Diffu │
│ 3025 │ if load_stable_diffusion_format: │
│ 3026 │ │ print(f"load StableDiffusion checkpoint: {name_or_path}") │
│ ❱ 3027 │ │ text_encoder, vae, unet = model_util.load_models_from_stable_diffusion_checkpoin │
│ 3028 │ else: │
│ 3029 │ │ # Diffusers model is loaded to CPU │
│ 3030 │ │ print(f"load Diffusers pretrained models: {name_or_path}") │
│ │
│ D:\kohya_ss\library\model_util.py:904 in load_models_from_stable_diffusion_checkpoint │
│ │
│ 901 │ │ converted_text_encoder_checkpoint = convert_ldm_clip_checkpoint_v1(state_dict) │
│ 902 │ │ │
│ 903 │ │ logging.set_verbosity_error() # don't show annoying warning │
│ ❱ 904 │ │ text_model = CLIPTextModel.from_pretrained("openai/clip-vit-large-patch14").to(d │
│ 905 │ │ logging.set_verbosity_warning() │
│ 906 │ │ │
│ 907 │ │ info = text_model.load_state_dict(converted_text_encoder_checkpoint) │
│ │
│ D:\kohya_ss\venv\lib\site-packages\transformers\modeling_utils.py:2222 in from_pretrained │
│ │
│ 2219 │ │ │ │ │ │ else: │
│ 2220 │ │ │ │ │ │ │ # This repo has no safetensors file of any kind, we switch t │
│ 2221 │ │ │ │ │ │ │ filename = WEIGHTS_NAME │
│ ❱ 2222 │ │ │ │ │ │ │ resolved_archive_file = cached_file( │
│ 2223 │ │ │ │ │ │ │ │ pretrained_model_name_or_path, WEIGHTS_NAME, **cached_fi │
│ 2224 │ │ │ │ │ │ │ ) │
│ 2225 │ │ │ │ │ if resolved_archive_file is None and filename == WEIGHTS_NAME: │
│ │
│ D:\kohya_ss\venv\lib\site-packages\transformers\utils\hub.py:409 in cached_file │
│ │
│ 406 │ user_agent = http_user_agent(user_agent) │
│ 407 │ try: │
│ 408 │ │ # Load from URL or cache if already cached │
│ ❱ 409 │ │ resolved_file = hf_hub_download( │
│ 410 │ │ │ path_or_repo_id, │
│ 411 │ │ │ filename, │
│ 412 │ │ │ subfolder=None if len(subfolder) == 0 else subfolder, │
│ │
│ D:\kohya_ss\venv\lib\site-packages\huggingface_hub\utils_validators.py:120 in _inner_fn │
│ │
│ 117 │ │ if check_use_auth_token: │
│ 118 │ │ │ kwargs = smoothly_deprecate_use_auth_token(fn_name=fn.name, has_token=ha │
│ 119 │ │ │
│ ❱ 120 │ │ return fn(*args, **kwargs) │
│ 121 │ │
│ 122 │ return _inner_fn # type: ignore │
│ 123 │
│ │
│ D:\kohya_ss\venv\lib\site-packages\huggingface_hub\file_download.py:1326 in hf_hub_download │
│ │
│ 1323 │ │ with temp_file_manager() as temp_file: │
│ 1324 │ │ │ logger.info("downloading %s to %s", url, temp_file.name) │
│ 1325 │ │ │ │
│ ❱ 1326 │ │ │ http_get( │
│ 1327 │ │ │ │ url_to_download, │
│ 1328 │ │ │ │ temp_file, │
│ 1329 │ │ │ │ proxies=proxies, │
│ │
│ D:\kohya_ss\venv\lib\site-packages\huggingface_hub\file_download.py:538 in http_get │
│ │
│ 535 │ │ desc=f"Downloading {displayed_name}", │
│ 536 │ │ disable=bool(logger.getEffectiveLevel() == logging.NOTSET), │
│ 537 │ ) │
│ ❱ 538 │ for chunk in r.iter_content(chunk_size=10 * 1024 * 1024): │
│ 539 │ │ if chunk: # filter out keep-alive new chunks │
│ 540 │ │ │ progress.update(len(chunk)) │
│ 541 │ │ │ temp_file.write(chunk) │
│ │
│ D:\kohya_ss\venv\lib\site-packages\requests\models.py:822 in generate │
│ │
│ 819 │ │ │ │ except DecodeError as e: │
│ 820 │ │ │ │ │ raise ContentDecodingError(e) │
│ 821 │ │ │ │ except ReadTimeoutError as e: │
│ ❱ 822 │ │ │ │ │ raise ConnectionError(e) │
│ 823 │ │ │ │ except SSLError as e: │
│ 824 │ │ │ │ │ raise RequestsSSLError(e) │
│ 825 │ │ │ else: │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
ConnectionError: HTTPSConnectionPool(host='cdn-lfs.huggingface.co', port=443): Read timed out.
Downloading pytorch_model.bin: 1%|▎ | 10.5M/1.71G [00:31<1:25:13, 332kB/s]
╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮
│ C:\Users\qqq99\AppData\Local\Programs\Python\Python310\lib\runpy.py:196 in _run_module_as_main │
│ │
│ 193 │ main_globals = sys.modules["main"].dict │
│ 194 │ if alter_argv: │
│ 195 │ │ sys.argv[0] = mod_spec.origin │
│ ❱ 196 │ return _run_code(code, main_globals, None, │
│ 197 │ │ │ │ │ "main", mod_spec) │
│ 198 │
│ 199 def run_module(mod_name, init_globals=None, │
│ │
│ C:\Users\qqq99\AppData\Local\Programs\Python\Python310\lib\runpy.py:86 in _run_code │
│ │
│ 83 │ │ │ │ │ loader = loader, │
│ 84 │ │ │ │ │ package = pkg_name, │
│ 85 │ │ │ │ │ spec = mod_spec) │
│ ❱ 86 │ exec(code, run_globals) │
│ 87 │ return run_globals │
│ 88 │
│ 89 def _run_module_code(code, init_globals=None, │
│ │
│ in :7 │
│ │
│ 4 from accelerate.commands.accelerate_cli import main │
│ 5 if name == 'main': │
│ 6 │ sys.argv[0] = re.sub(r'(-script.pyw|.exe)?$', '', sys.argv[0]) │
│ ❱ 7 │ sys.exit(main()) │
│ 8 │
│ │
│ D:\kohya_ss\venv\lib\site-packages\accelerate\commands\accelerate_cli.py:45 in main │
│ │
│ 42 │ │ exit(1) │
│ 43 │ │
│ 44 │ # Run │
│ ❱ 45 │ args.func(args) │
│ 46 │
│ 47 │
│ 48 if name == "main": │
│ │
│ D:\kohya_ss\venv\lib\site-packages\accelerate\commands\launch.py:1104 in launch_command │
│ │
│ 1101 │ elif defaults is not None and defaults.compute_environment == ComputeEnvironment.AMA │
│ 1102 │ │ sagemaker_launcher(defaults, args) │
│ 1103 │ else: │
│ ❱ 1104 │ │ simple_launcher(args) │
│ 1105 │
│ 1106 │
│ 1107 def main(): │
│ │
│ D:\kohya_ss\venv\lib\site-packages\accelerate\commands\launch.py:567 in simple_launcher │
│ │
│ 564 │ process = subprocess.Popen(cmd, env=current_env) │
│ 565 │ process.wait() │
│ 566 │ if process.returncode != 0: │
│ ❱ 567 │ │ raise subprocess.CalledProcessError(returncode=process.returncode, cmd=cmd) │
│ 568 │
│ 569 │
│ 570 def multi_gpu_launcher(args): │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
CalledProcessError: Command '['D:\kohya_ss\venv\Scripts\python.exe', 'train_network.py',
'--pretrained_model_name_or_path=D:/stable
diffusion/stable-diffusion-webui/models/Stable-diffusion/v1-5-pruned.safetensors', '--train_data_dir=D:/stable
diffusion/pre/', '--resolution=512,512', '--output_dir=D:/stable diffusion/pre/OtPut', '--network_alpha=128',
'--save_model_as=safetensors', '--network_module=networks.lora', '--text_encoder_lr=5e-05', '--unet_lr=0.0001',
'--network_dim=128', '--output_name=asian', '--lr_scheduler_num_cycles=1', '--learning_rate=0.0001',
'--lr_scheduler=constant', '--train_batch_size=1', '--max_train_steps=7600', '--save_every_n_epochs=1',
'--mixed_precision=fp16', '--save_precision=fp16', '--seed=1234', '--caption_extension=.txt', '--cache_latents',
'--optimizer_type=AdamW', '--max_data_loader_n_workers=1', '--clip_skip=2', '--bucket_reso_steps=64', '--mem_eff_attn',
'--gradient_checkpointing', '--xformers', '--bucket_no_upscale']' returned non-zero exit status 1.