How to investigate "CAS service error" during model downloading?
Author: satyrmipt
Pull request: no
Labels: name: bug

### System Info


(nm) PS C:\Users\myuser\AppData\Local\anaconda3\envs\nm\Lib\site-packages\transformers\commands> python .\transformers_cli.py env

```
Copy-and-paste the text below in your GitHub issue and FILL OUT the two last points.

- `transformers` version: 4.57.3
- Platform: Windows-10-10.0.19045-SP0
- Python version: 3.10.19
- Huggingface_hub version: 0.36.0
- Safetensors version: 0.7.0
- Accelerate version: not installed
- Accelerate config: not found
- DeepSpeed version: not installed
- PyTorch version (accelerator?): 2.7.0 (NA)
- Tensorflow version (GPU?): not installed (NA)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using distributed or parallel set-up in script?:  the whole code posted below
```

### Who can help?

_No response_

### Information

- [ ] The official example scripts
- [x] My own modified scripts

### Tasks

- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)

### Reproduction

Base example from [here](https://huggingface.co/cross-encoder/ms-marco-MiniLM-L6-v2) 

```
from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch

model = AutoModelForSequenceClassification.from_pretrained('cross-encoder/ms-marco-MiniLM-L6-v2')
tokenizer = AutoTokenizer.from_pretrained('cross-encoder/ms-marco-MiniLM-L6-v2')

features = tokenizer(['How many people live in Berlin?', 'How many people live in Berlin?'], ['Berlin has a population of 3,520,031 registered inhabitants in an area of 891.82 square kilometers.', 'New York City is famous for the Metropolitan Museum of Art.'],  padding=True, truncation=True, return_tensors="pt")

model.eval()
with torch.no_grad():
    scores = model(**features).logits
    print(scores)
```

returns

```
model.safetensors:   0%
 0.00/90.9M [00:32<?, ?B/s]
---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
File c:\Users\myuser\AppData\Local\anaconda3\envs\nm\lib\site-packages\transformers\modeling_utils.py:1037, in _get_resolved_checkpoint_files(pretrained_model_name_or_path, subfolder, variant, gguf_file, from_tf, from_flax, use_safetensors, cache_dir, force_download, proxies, local_files_only, token, user_agent, revision, commit_hash, is_remote_code, transformers_explicit_filename)
   1024 cached_file_kwargs = {
   1025     "cache_dir": cache_dir,
   1026     "force_download": force_download,
   (...)
   1035     "_commit_hash": commit_hash,
   1036 }
-> [1037](file:///C:/Users/myuser	/AppData/Local/anaconda3/envs/nm/lib/site-packages/transformers/modeling_utils.py:1037) resolved_archive_file = cached_file(pretrained_model_name_or_path, filename, **cached_file_kwargs)
   1039 # Since we set _raise_exceptions_for_missing_entries=False, we don't get an exception but a None
   1040 # result when internet is up, the repo and revision exist, but the file does not.

File c:\Users\myuser\AppData\Local\anaconda3\envs\nm\lib\site-packages\transformers\utils\hub.py:322, in cached_file(path_or_repo_id, filename, **kwargs)
    269 """
    270 Tries to locate a file in a local folder and repo, downloads and cache it if necessary.
    271 
   (...)
    320 ```
    321 """
--> [322](file:///C:/Users/myuser	/AppData/Local/anaconda3/envs/nm/lib/site-packages/transformers/utils/hub.py:322) file = cached_files(path_or_repo_id=path_or_repo_id, filenames=[filename], **kwargs)
    323 file = file[0] if file is not None else file

File c:\Users\myuser\AppData\Local\anaconda3\envs\nm\lib\site-packages\transformers\utils\hub.py:567, in cached_files(path_or_repo_id, filenames, cache_dir, force_download, resume_download, proxies, token, revision, local_files_only, subfolder, repo_type, user_agent, _raise_exceptions_for_gated_repo, _raise_exceptions_for_missing_entries, _raise_exceptions_for_connection_errors, _commit_hash, **deprecated_kwargs)
    566     elif not isinstance(e, EntryNotFoundError):
--> [567](file:///C:/Users/myuser	/AppData/Local/anaconda3/envs/nm/lib/site-packages/transformers/utils/hub.py:567)         raise e
    569 resolved_files = [
    570     _get_cache_file_to_return(path_or_repo_id, filename, cache_dir, revision) for filename in full_filenames
    571 ]

File c:\Users\myuser\AppData\Local\anaconda3\envs\nm\lib\site-packages\transformers\utils\hub.py:479, in cached_files(path_or_repo_id, filenames, cache_dir, force_download, resume_download, proxies, token, revision, local_files_only, subfolder, repo_type, user_agent, _raise_exceptions_for_gated_repo, _raise_exceptions_for_missing_entries, _raise_exceptions_for_connection_errors, _commit_hash, **deprecated_kwargs)
    477 if len(full_filenames) == 1:
    478     # This is slightly better for only 1 file
--> [479](file:///C:/Users/myuser	/AppData/Local/anaconda3/envs/nm/lib/site-packages/transformers/utils/hub.py:479)     hf_hub_download(
    480         path_or_repo_id,
    481         filenames[0],
    482         subfolder=None if len(subfolder) == 0 else subfolder,
    483         repo_type=repo_type,
    484         revision=revision,
    485         cache_dir=cache_dir,
    486         user_agent=user_agent,
    487         force_download=force_download,
    488         proxies=proxies,
    489         resume_download=resume_download,
    490         token=token,
    491         local_files_only=local_files_only,
    492     )
    493 else:

File c:\Users\myuser\AppData\Local\anaconda3\envs\nm\lib\site-packages\huggingface_hub\utils\_validators.py:[114](file:///C:/Users/myuser	/AppData/Local/anaconda3/envs/nm/lib/site-packages/huggingface_hub/utils/_validators.py:114), in validate_hf_hub_args.<locals>._inner_fn(*args, **kwargs)
    112     kwargs = smoothly_deprecate_use_auth_token(fn_name=fn.__name__, has_token=has_token, kwargs=kwargs)
--> 114 return fn(*args, **kwargs)

File c:\Users\myuser\AppData\Local\anaconda3\envs\nm\lib\site-packages\huggingface_hub\file_download.py:1007, in hf_hub_download(repo_id, filename, subfolder, repo_type, revision, library_name, library_version, cache_dir, local_dir, user_agent, force_download, proxies, etag_timeout, token, local_files_only, headers, endpoint, resume_download, force_filename, local_dir_use_symlinks)
   1006 else:
-> [1007](file:///C:/Users/myuser	/AppData/Local/anaconda3/envs/nm/lib/site-packages/huggingface_hub/file_download.py:1007)     return _hf_hub_download_to_cache_dir(
   1008         # Destination
   1009         cache_dir=cache_dir,
   1010         # File info
   1011         repo_id=repo_id,
   1012         filename=filename,
   1013         repo_type=repo_type,
   1014         revision=revision,
   1015         # HTTP info
   1016         endpoint=endpoint,
   1017         etag_timeout=etag_timeout,
   1018         headers=hf_headers,
   1019         proxies=proxies,
   1020         token=token,
   1021         # Additional options
   1022         local_files_only=local_files_only,
   1023         force_download=force_download,
   1024     )

File c:\Users\myuser\AppData\Local\anaconda3\envs\nm\lib\site-packages\huggingface_hub\file_download.py:[1168](file:///C:/Users/myuser	/AppData/Local/anaconda3/envs/nm/lib/site-packages/huggingface_hub/file_download.py:1168), in _hf_hub_download_to_cache_dir(cache_dir, repo_id, filename, repo_type, revision, endpoint, etag_timeout, headers, proxies, token, local_files_only, force_download)
   1167 with WeakFileLock(lock_path):
-> 1168     _download_to_tmp_and_move(
   1169         incomplete_path=Path(blob_path + ".incomplete"),
   1170         destination_path=Path(blob_path),
   1171         url_to_download=url_to_download,
   1172         proxies=proxies,
   1173         headers=headers,
   1174         expected_size=expected_size,
   1175         filename=filename,
   1176         force_download=force_download,
   1177         etag=etag,
   1178         xet_file_data=xet_file_data,
   1179     )
   1180     if not os.path.exists(pointer_path):

File c:\Users\myuser\AppData\Local\anaconda3\envs\nm\lib\site-packages\huggingface_hub\file_download.py:[1720](file:///C:/Users/myuser	/AppData/Local/anaconda3/envs/nm/lib/site-packages/huggingface_hub/file_download.py:1720), in _download_to_tmp_and_move(incomplete_path, destination_path, url_to_download, proxies, headers, expected_size, filename, force_download, etag, xet_file_data)
   1719     logger.debug("Xet Storage is enabled for this repo. Downloading file from Xet Storage..")
-> 1720     xet_get(
   1721         incomplete_path=incomplete_path,
   1722         xet_file_data=xet_file_data,
   1723         headers=headers,
   1724         expected_size=expected_size,
   1725         displayed_filename=filename,
   1726     )
   1727 else:

File c:\Users\myuser\AppData\Local\anaconda3\envs\nm\lib\site-packages\huggingface_hub\file_download.py:[626](file:///C:/Users/myuser	/AppData/Local/anaconda3/envs/nm/lib/site-packages/huggingface_hub/file_download.py:626), in xet_get(incomplete_path, xet_file_data, headers, expected_size, displayed_filename, _tqdm_bar)
    624     progress.update(progress_bytes)
--> 626 download_files(
    627     xet_download_info,
    628     endpoint=connection_info.endpoint,
    629     token_info=(connection_info.access_token, connection_info.expiration_unix_epoch),
    630     token_refresher=token_refresher,
    631     progress_updater=[progress_updater],
    632 )

RuntimeError: Data processing error: CAS service error : ReqwestMiddleware Error: Request failed after 5 retries

The above exception was the direct cause of the following exception:

OSError                                   Traceback (most recent call last)
Cell In[1], [line 4](vscode-notebook-cell:?execution_count=1&line=4)
      1 from transformers import AutoTokenizer, AutoModelForSequenceClassification
      2 import torch
----> [4](vscode-notebook-cell:?execution_count=1&line=4) model = AutoModelForSequenceClassification.from_pretrained('cross-encoder/ms-marco-MiniLM-L6-v2')
      5 tokenizer = AutoTokenizer.from_pretrained('cross-encoder/ms-marco-MiniLM-L6-v2')
      7 features = tokenizer(['How many people live in Berlin?', 'How many people live in Berlin?'], ['Berlin has a population of 3,520,031 registered inhabitants in an area of 891.82 square kilometers.', 'New York City is famous for the Metropolitan Museum of Art.'],  padding=True, truncation=True, return_tensors="pt")

File c:\Users\myuser\AppData\Local\anaconda3\envs\nm\lib\site-packages\transformers\models\auto\auto_factory.py:604, in _BaseAutoModelClass.from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs)
    602     if model_class.config_class == config.sub_configs.get("text_config", None):
    603         config = config.get_text_config()
--> [604](file:///C:/Users/myuser	/AppData/Local/anaconda3/envs/nm/lib/site-packages/transformers/models/auto/auto_factory.py:604)     return model_class.from_pretrained(
    605         pretrained_model_name_or_path, *model_args, config=config, **hub_kwargs, **kwargs
    606     )
    607 raise ValueError(
    608     f"Unrecognized configuration class {config.__class__} for this kind of AutoModel: {cls.__name__}.\n"
    609     f"Model type should be one of {', '.join(c.__name__ for c in cls._model_mapping)}."
    610 )

File c:\Users\myuser\AppData\Local\anaconda3\envs\nm\lib\site-packages\transformers\modeling_utils.py:277, in restore_default_dtype.<locals>._wrapper(*args, **kwargs)
    275 old_dtype = torch.get_default_dtype()
    276 try:
--> [277](file:///C:/Users/myuser	/AppData/Local/anaconda3/envs/nm/lib/site-packages/transformers/modeling_utils.py:277)     return func(*args, **kwargs)
    278 finally:
    279     torch.set_default_dtype(old_dtype)

File c:\Users\myuser\AppData\Local\anaconda3\envs\nm\lib\site-packages\transformers\modeling_utils.py:4900, in PreTrainedModel.from_pretrained(cls, pretrained_model_name_or_path, config, cache_dir, ignore_mismatched_sizes, force_download, local_files_only, token, revision, use_safetensors, weights_only, *model_args, **kwargs)
   4890 if (
   4891     gguf_file
   4892     and device_map is not None
   4893     and ((isinstance(device_map, dict) and "disk" in device_map.values()) or "disk" in device_map)
   4894 ):
   4895     raise RuntimeError(
   4896         "One or more modules is configured to be mapped to disk. Disk offload is not supported for models "
   4897         "loaded from GGUF files."
   4898     )
-> [4900](file:///C:/Users/myuser	/AppData/Local/anaconda3/envs/nm/lib/site-packages/transformers/modeling_utils.py:4900) checkpoint_files, sharded_metadata = _get_resolved_checkpoint_files(
   4901     pretrained_model_name_or_path=pretrained_model_name_or_path,
   4902     subfolder=subfolder,
   4903     variant=variant,
   4904     gguf_file=gguf_file,
   4905     from_tf=from_tf,
   4906     from_flax=from_flax,
   4907     use_safetensors=use_safetensors,
   4908     cache_dir=cache_dir,
   4909     force_download=force_download,
   4910     proxies=proxies,
   4911     local_files_only=local_files_only,
   4912     token=token,
   4913     user_agent=user_agent,
   4914     revision=revision,
   4915     commit_hash=commit_hash,
   4916     is_remote_code=cls._auto_class is not None,
   4917     transformers_explicit_filename=transformers_explicit_filename,
   4918 )
   4920 is_sharded = sharded_metadata is not None
   4921 is_quantized = hf_quantizer is not None

File c:\Users\myuser\AppData\Local\anaconda3\envs\nm\lib\site-packages\transformers\modeling_utils.py:1160, in _get_resolved_checkpoint_files(pretrained_model_name_or_path, subfolder, variant, gguf_file, from_tf, from_flax, use_safetensors, cache_dir, force_download, proxies, local_files_only, token, user_agent, revision, commit_hash, is_remote_code, transformers_explicit_filename)
   1157         raise
   1158     except Exception as e:
   1159         # For any other exception, we throw a generic error.
-> [1160](file:///C:/Users/myuser	/AppData/Local/anaconda3/envs/nm/lib/site-packages/transformers/modeling_utils.py:1160)         raise OSError(
   1161             f"Can't load the model for '{pretrained_model_name_or_path}'. If you were trying to load it"
   1162             " from 'https://huggingface.co/models', make sure you don't have a local directory with the"
   1163             f" same name. Otherwise, make sure '{pretrained_model_name_or_path}' is the correct path to a"
   1164             f" directory containing a file named {_add_variant(WEIGHTS_NAME, variant)},"
   1165             f" {TF2_WEIGHTS_NAME}, {TF_WEIGHTS_NAME} or {FLAX_WEIGHTS_NAME}."
   1166         ) from e
   1168 if is_local:
   1169     logger.info(f"loading weights file {archive_file}")

OSError: Can't load the model for 'cross-encoder/ms-marco-MiniLM-L6-v2'. If you were trying to load it from 'https://huggingface.co/models', ma
```

OS environments:
```
# import os
# for key, value in os.environ.items():
#     if ('HF' in key) or ('CAS' in key) or ('HTTP' in key) or ('CA' in key) or ('SSL' in key) or ('TLS' in key):
#         print(f"{key}: {value}")

APPLICATION_INSIGHTS_NO_STATSBEAT: true
LOCALAPPDATA: C:\Users\myuser\AppData\Local
SSL_CERT_DIR: C:\Users\myuser\AppData\Local\anaconda3\envs\nm\Library\ssl\certs
SSL_CERT_FILE: C:\Users\myuser\AppData\Local\anaconda3\envs\nm\Library\ssl\cacert.pem
VSCODE_CODE_CACHE_PATH: C:\Users\myuser\AppData\Roaming\Code\CachedData\994fd12f8d3a5aa16f17d42c041e5809167e845a
VSCODE_HANDLES_UNCAUGHT_ERRORS: true
VSCODE_L10N_BUNDLE_LOCATION: 
__CONDA_OPENSSL_CERT_DIR_SET: 1
__CONDA_OPENSSL_CERT_FILE_SET: 1
KMP_DUPLICATE_LIB_OK: True

```

`transformers_cli.py env` output:

(nm) PS C:\Users\myuser\AppData\Local\anaconda3\envs\nm\Lib\site-packages\transformers\commands> python .\transformers_cli.py env

```
Copy-and-paste the text below in your GitHub issue and FILL OUT the two last points.

- `transformers` version: 4.57.3
- Platform: Windows-10-10.0.19045-SP0
- Python version: 3.10.19
- Huggingface_hub version: 0.36.0
- Safetensors version: 0.7.0
- Accelerate version: not installed
- Accelerate config: not found
- DeepSpeed version: not installed
- PyTorch version (accelerator?): 2.7.0 (NA)
- Tensorflow version (GPU?): not installed (NA)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using distributed or parallel set-up in script?:  the whole code posted below
```

environment definition: see reqirements.txt in attachment 

inspite of i'm on win machine, cygwin allows me to use nslookup which is risky trick but i dont have the same command for windows.
`$ openssl s_client -showcerts -connect huggingface.co:443`

```
CONNECTED(00000004)
depth=2 C = US, O = Amazon, CN = Amazon Root CA 1
verify return:1
depth=1 C = US, O = Amazon, CN = Amazon RSA 2048 M02
verify return:1
depth=0 CN = huggingface.co
verify return:1
---
Certificate chain
 0 s:CN = huggingface.co
   i:C = US, O = Amazon, CN = Amazon RSA 2048 M02
   a:PKEY: rsaEncryption, 2048 (bit); sigalg: RSA-SHA256
   v:NotBefore: Apr 13 00:00:00 2025 GMT; NotAfter: May 12 23:59:59 2026 GMT
-----BEGIN CERTIFICATE-----
MIIF2jCC blah blah
-----END CERTIFICATE-----
 1 s:C = US, O = Amazon, CN = Amazon RSA 2048 M02
   i:C = US, O = Amazon, CN = Amazon Root CA 1
   a:PKEY: rsaEncryption, 2048 (bit); sigalg: RSA-SHA256
   v:NotBefore: Aug 23 22:25:30 2022 GMT; NotAfter: Aug 23 22:25:30 2030 GMT
-----BEGIN CERTIFICATE-----
MIIEXjCC  blah blah
-----END CERTIFICATE-----
 2 s:C = US, O = Amazon, CN = Amazon Root CA 1
   i:C = US, ST = Arizona, L = Scottsdale, O = "Starfield Technologies, Inc.", CN = Starfield Services Root Certificate Authority - G2
   a:PKEY: rsaEncryption, 2048 (bit); sigalg: RSA-SHA256
   v:NotBefore: May 25 12:00:00 2015 GMT; NotAfter: Dec 31 01:00:00 2037 GMT
-----BEGIN CERTIFICATE-----
MIIEkjCCA3qgA blah blah
-----END CERTIFICATE-----
---
Server certificate
subject=CN = huggingface.co
issuer=C = US, O = Amazon, CN = Amazon RSA 2048 M02
---
No client certificate CA names sent
Peer signing digest: SHA256
Peer signature type: RSA-PSS
Server Temp Key: X25519, 253 bits
---
SSL handshake has read 4352 bytes and written 400 bytes
Verification: OK
---
New, TLSv1.3, Cipher is TLS_AES_128_GCM_SHA256
Server public key is 2048 bit
Secure Renegotiation IS NOT supported
Compression: NONE
Expansion: NONE
No ALPN negotiated
Early data was not sent
Verify return code: 0 (ok)
---
---
Post-Handshake New Session Ticket arrived:
SSL-Session:
    Protocol  : TLSv1.3
    Cipher    : TLS_AES_128_GCM_SHA256
    Session-ID: 3B1B36B2902CB52F573D54B4D423F5E4140D6ACD07E09E52DE145FC206E2C652
    Session-ID-ctx:
    Resumption PSK: BF0DC1244120B771DB3390206F04A7A0EF673B071A4A1EA559EF405DB50B60BC
    PSK identity: None
    PSK identity hint: None
    SRP username: None
    TLS session ticket lifetime hint: 52055 (seconds)
    TLS session ticket:
    0000 - 01 31 37 36 36 34 36 35-35 35 39 30 30 30 00 00   .1766465559000..
    0010 - 00 2c 21 5e 39 97 17 5e-be 5d d8 43 e6 13 9a 12   .,!^9..^.].C....
    0020 - c3 07 7f 06 48 2a 22 64-d3 71 14 d4 10 2a b5 67   ....H*"d.q...*.g
    0030 - 4a cb b2 82 83 59 46 55-0f 65 04 b0 6f db 00 05   J....YFU.e..o...
    0040 - 01 06 1b d6 af 78 21 86-8f ca 5c 57 1a 85 e7 36   .....x!...\W...6
    0050 - 6e d7 1c 9a f0 dd 01 e0-81 fa 81 18 c1 c7 0d 19   n...............
    0060 - b1 fd ce 26 22 39 f1 19-78 8b 07 1a 9a bd f9 17   ...&"9..x.......
    0070 - 56 99 5d 88 eb 11 24 53-ba a6 88 cf 6e 91 59 b4   V.]...$S....n.Y.
    0080 - f1 e4 36 3e 9b 9c 41 b8-89 a9                     ..6>..A...

    Start Time: 1766499903
    Timeout   : 7200 (sec)
    Verify return code: 0 (ok)
    Extended master secret: no
    Max Early Data: 0
---
read R BLOCK
closed

```

transformers was installed through `conda install -c conda-forge sentence-transformers`

[requirements.txt](https://github.com/user-attachments/files/24312527/requirements.txt)

### Expected behavior

model is downloaded and ready to use 

Comments:
Your connection to `huggingface.co` works, but XET uses separate endpoints. Can you test connectivity to the XET endpoints? As a quick workaround, try disabling XET by setting HF_HUB_DISABLE_XET. 

@junjunjd , please list XET endpoints adresses or approve the list below:

```
cas-server.hf.co
transfer.xethub.hf.co
cas-bridge.xethub.hf.co
```

The error have no information about it except for cas-bridge.xethub.hf.co.
I unistalled XET (i did it before you recommend to disable XET by setting HF_HUB_DISABLE_XET) hence my current configuration is:


```
C:\Users\myuser\AppData\Local\anaconda3\envs\nm\Lib\site-packages\transformers\commands> python .\transformers_cli.py env

Copy-and-paste the text below in your GitHub issue and FILL OUT the two last points.

- `transformers` version: 4.57.3
- Platform: Windows-10-10.0.19045-SP0
- Python version: 3.10.19
- Huggingface_hub version: 0.36.0
- Safetensors version: 0.7.0
- Accelerate version: not installed
- Accelerate config: not found
- DeepSpeed version: not installed
- PyTorch version (accelerator?): 2.7.0 (NA)
- Tensorflow version (GPU?): not installed (NA)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using distributed or parallel set-up in script?: <fill in>
```

then tried 

`model = AutoModelForSequenceClassification.from_pretrained('cross-encoder/ms-marco-MiniLM-L6-v2')`

again and get this error:

```
Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
'(MaxRetryError("HTTPSConnectionPool(host='cas-bridge.xethub.hf.co', port=443): Max retries exceeded with url: /xet-bridge-us/621ff........ (Caused by SSLError(SSLCertVerificationError(1, '[SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: unable to get local issuer certificate (_ssl.c:1017)')))"), '(Request ID: 7392d356-6923-4bf2-934d-5cd501152d0d)')' thrown while requesting GET https://huggingface.co/cross-encoder/ms-marco-MiniLM-L6-v2/resolve/main/model.safetensors
Retrying in 1s [Retry 1/5].
```

So i check cas-bridge.xethub.hf.co availability and got this:

without -proxy parameter:
```
$ openssl s_client -showcerts -connect cas-bridge.xethub.hf.co
100000000A000000:error:80000074:system library:BIO_connect:Connection timed out:crypto/bio/bio_sock2.c:114:calling connect()
100000000A000000:error:10000067:BIO routines:BIO_connect:connect error:crypto/bio/bio_sock2.c:116:
100000000A000000:error:80000074:system library:BIO_connect:Connection timed out:crypto/bio/bio_sock2.c:114:calling connect()
100000000A000000:error:10000067:BIO routines:BIO_connect:connect error:crypto/bio/bio_sock2.c:116:
100000000A000000:error:80000074:system library:BIO_connect:Connection timed out:crypto/bio/bio_sock2.c:114:calling connect()
100000000A000000:error:10000067:BIO routines:BIO_connect:connect error:crypto/bio/bio_sock2.c:116:
100000000A000000:error:80000074:system library:BIO_connect:Connection timed out:crypto/bio/bio_sock2.c:114:calling connect()
100000000A000000:error:10000067:BIO routines:BIO_connect:connect error:crypto/bio/bio_sock2.c:116:
connect:errno=116
```

with -proxy parameter:

```
$ openssl s_client -showcerts -connect cas-bridge.xethub.hf.co -proxy my_porxy:proxy_port
CONNECTED(00000004)
s_client: HTTP CONNECT failed, reason= 403 Forbidden
---
no peer certificate available
---
No client certificate CA names sent
---
SSL handshake has read 3439 bytes and written 79 bytes
Verification: OK
---
New, (NONE), Cipher is (NONE)
Secure Renegotiation IS NOT supported
Compression: NONE
Expansion: NONE
No ALPN negotiated
Early data was not sent
Verify return code: 0 (ok)
---
```
What does this "403 Forbidden" mean? Is it forbidden due to sertificates problem on my side, or sertificate problem is due to access is forbidden?

The same story for `transfer.xethub.hf.co`  and `cas-server.hf.co`






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