Add doc + pass kwarg everywhere

src/transformers/configuration_auto.py

@@ -289,6 +289,10 @@ def from_pretrained(cls, pretrained_model_name_or_path, **kwargs):
             proxies (:obj:`Dict[str, str]`, `optional`):
                 A dictionary of proxy servers to use by protocol or endpoint, e.g., :obj:`{'http': 'foo.bar:3128',
                 'http://hostname': 'foo.bar:4012'}`. The proxies are used on each request.
+            revision(:obj:`str`, `optional`, defaults to :obj:`"main"`):
+                The specific model version to use. It can be a branch name, a tag name, or a commit id, since we use a
+                git-based system for storing models and other artifacts on huggingface.co, so ``revision`` can be any
+                identifier allowed by git.
             return_unused_kwargs (:obj:`bool`, `optional`, defaults to :obj:`False`):
                 If :obj:`False`, then this function returns just the final configuration object.
 

src/transformers/configuration_utils.py

@@ -311,6 +311,10 @@ def from_pretrained(cls, pretrained_model_name_or_path: str, **kwargs) -> "Pretr
             proxies (:obj:`Dict[str, str]`, `optional`):
                 A dictionary of proxy servers to use by protocol or endpoint, e.g., :obj:`{'http': 'foo.bar:3128',
                 'http://hostname': 'foo.bar:4012'}.` The proxies are used on each request.
+            revision(:obj:`str`, `optional`, defaults to :obj:`"main"`):
+                The specific model version to use. It can be a branch name, a tag name, or a commit id, since we use a
+                git-based system for storing models and other artifacts on huggingface.co, so ``revision`` can be any
+                identifier allowed by git.
             return_unused_kwargs (:obj:`bool`, `optional`, defaults to :obj:`False`):
                 If :obj:`False`, then this function returns just the final configuration object.
 

src/transformers/modeling_flax_utils.py

@@ -107,6 +107,7 @@ def from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs):
         proxies = kwargs.pop("proxies", None)
         # output_loading_info = kwargs.pop("output_loading_info", False)
         local_files_only = kwargs.pop("local_files_only", False)
+        revision = kwargs.pop("revision", None)
 
         # Load config if we don't provide a configuration
         if not isinstance(config, PretrainedConfig):
@@ -120,6 +121,7 @@ def from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs):
                 resume_download=resume_download,
                 proxies=proxies,
                 local_files_only=local_files_only,
+                revision=revision,
                 **kwargs,
             )
         else:
@@ -130,7 +132,7 @@ def from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs):
             if os.path.isfile(pretrained_model_name_or_path) or is_remote_url(pretrained_model_name_or_path):
                 archive_file = pretrained_model_name_or_path
             else:
-                archive_file = hf_bucket_url(pretrained_model_name_or_path, filename=WEIGHTS_NAME)
+                archive_file = hf_bucket_url(pretrained_model_name_or_path, filename=WEIGHTS_NAME, revision=revision)
 
             # redirect to the cache, if necessary
             try:
@@ -142,16 +144,13 @@ def from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs):
                     resume_download=resume_download,
                     local_files_only=local_files_only,
                 )
-            except EnvironmentError:
-                if pretrained_model_name_or_path in cls.pretrained_model_archive_map:
-                    msg = f"Couldn't reach server at '{archive_file}' to download pretrained weights."
-                else:
-                    msg = (
-                        f"Model name '{pretrained_model_name_or_path}' "
-                        f"was not found in model name list ({', '.join(cls.pretrained_model_archive_map.keys())}). "
-                        f"We assumed '{archive_file}' was a path or url to model weight files but "
-                        "couldn't find any such file at this path or url."
-                    )
+            except EnvironmentError as err:
+                logger.error(err)
+                msg = (
+                    f"Can't load weights for '{pretrained_model_name_or_path}'. Make sure that:\n\n"
+                    f"- '{pretrained_model_name_or_path}' is a correct model identifier listed on 'https://huggingface.co/models'\n\n"
+                    f"- or '{pretrained_model_name_or_path}' is the correct path to a directory containing a file named one of {TF2_WEIGHTS_NAME}, {WEIGHTS_NAME}.\n\n"
+                )
                 raise EnvironmentError(msg)
 
             if resolved_archive_file == archive_file:

src/transformers/modeling_tf_auto.py

@@ -416,6 +416,10 @@
                 Whether ot not to also return a dictionary containing missing keys, unexpected keys and error messages.
             local_files_only(:obj:`bool`, `optional`, defaults to :obj:`False`):
                 Whether or not to only look at local files (e.g., not try downloading the model).
+            revision(:obj:`str`, `optional`, defaults to :obj:`"main"`):
+                The specific model version to use. It can be a branch name, a tag name, or a commit id, since we use a
+                git-based system for storing models and other artifacts on huggingface.co, so ``revision`` can be any
+                identifier allowed by git.
             kwargs (additional keyword arguments, `optional`):
                 Can be used to update the configuration object (after it being loaded) and initiate the model (e.g.,
                 :obj:`output_attentions=True`). Behaves differently depending on whether a ``config`` is provided or

src/transformers/modeling_tf_utils.py

@@ -572,6 +572,10 @@ def from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs):
                 Whether ot not to also return a dictionary containing missing keys, unexpected keys and error messages.
             local_files_only(:obj:`bool`, `optional`, defaults to :obj:`False`):
                 Whether or not to only look at local files (e.g., not try doanloading the model).
+            revision(:obj:`str`, `optional`, defaults to :obj:`"main"`):
+                The specific model version to use. It can be a branch name, a tag name, or a commit id, since we use a
+                git-based system for storing models and other artifacts on huggingface.co, so ``revision`` can be any
+                identifier allowed by git.
             mirror(:obj:`str`, `optional`, defaults to :obj:`None`):
                 Mirror source to accelerate downloads in China. If you are from China and have an accessibility
                 problem, you can set this option to resolve it. Note that we do not guarantee the timeliness or safety.
@@ -613,6 +617,7 @@ def from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs):
         proxies = kwargs.pop("proxies", None)
         output_loading_info = kwargs.pop("output_loading_info", False)
         local_files_only = kwargs.pop("local_files_only", False)
+        revision = kwargs.pop("revision", None)
         mirror = kwargs.pop("mirror", None)
 
         # Load config if we don't provide a configuration
@@ -627,6 +632,7 @@ def from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs):
                 resume_download=resume_download,
                 proxies=proxies,
                 local_files_only=local_files_only,
+                revision=revision,
                 **kwargs,
             )
         else:
@@ -655,6 +661,7 @@ def from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs):
                 archive_file = hf_bucket_url(
                     pretrained_model_name_or_path,
                     filename=(WEIGHTS_NAME if from_pt else TF2_WEIGHTS_NAME),
+                    revision=revision,
                     mirror=mirror,
                 )
 

src/transformers/modeling_utils.py

@@ -813,6 +813,10 @@ def from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs):
                 Whether ot not to also return a dictionary containing missing keys, unexpected keys and error messages.
             local_files_only(:obj:`bool`, `optional`, defaults to :obj:`False`):
                 Whether or not to only look at local files (e.g., not try doanloading the model).
+            revision(:obj:`str`, `optional`, defaults to :obj:`"main"`):
+                The specific model version to use. It can be a branch name, a tag name, or a commit id, since we use a
+                git-based system for storing models and other artifacts on huggingface.co, so ``revision`` can be any
+                identifier allowed by git.
             mirror(:obj:`str`, `optional`, defaults to :obj:`None`):
                 Mirror source to accelerate downloads in China. If you are from China and have an accessibility
                 problem, you can set this option to resolve it. Note that we do not guarantee the timeliness or safety.
@@ -869,6 +873,7 @@ def from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs):
                 resume_download=resume_download,
                 proxies=proxies,
                 local_files_only=local_files_only,
+                revision=revision,
                 **kwargs,
             )
         else:

src/transformers/tokenization_auto.py

@@ -276,6 +276,10 @@ def from_pretrained(cls, pretrained_model_name_or_path, *inputs, **kwargs):
             proxies (:obj:`Dict[str, str]`, `optional`):
                 A dictionary of proxy servers to use by protocol or endpoint, e.g., :obj:`{'http': 'foo.bar:3128',
                 'http://hostname': 'foo.bar:4012'}`. The proxies are used on each request.
+            revision(:obj:`str`, `optional`, defaults to :obj:`"main"`):
+                The specific model version to use. It can be a branch name, a tag name, or a commit id, since we use a
+                git-based system for storing models and other artifacts on huggingface.co, so ``revision`` can be any
+                identifier allowed by git.
             use_fast (:obj:`bool`, `optional`, defaults to :obj:`False`):
                 Whether or not to try to load the fast version of the tokenizer.
             kwargs (additional keyword arguments, `optional`):

src/transformers/tokenization_utils_base.py

@@ -1517,6 +1517,10 @@ def from_pretrained(cls, pretrained_model_name_or_path, *init_inputs, **kwargs):
             proxies (:obj:`Dict[str, str], `optional`):
                 A dictionary of proxy servers to use by protocol or endpoint, e.g., :obj:`{'http': 'foo.bar:3128',
                 'http://hostname': 'foo.bar:4012'}`. The proxies are used on each request.
+            revision(:obj:`str`, `optional`, defaults to :obj:`"main"`):
+                The specific model version to use. It can be a branch name, a tag name, or a commit id, since we use a
+                git-based system for storing models and other artifacts on huggingface.co, so ``revision`` can be any
+                identifier allowed by git.
             inputs (additional positional arguments, `optional`):
                 Will be passed along to the Tokenizer ``__init__`` method.
             kwargs (additional keyword arguments, `optional`):
@@ -1551,6 +1555,7 @@ def from_pretrained(cls, pretrained_model_name_or_path, *init_inputs, **kwargs):
         resume_download = kwargs.pop("resume_download", False)
         proxies = kwargs.pop("proxies", None)
         local_files_only = kwargs.pop("local_files_only", False)
+        revision = kwargs.pop("revision", None)
 
         s3_models = list(cls.max_model_input_sizes.keys())
         vocab_files = {}
@@ -1602,7 +1607,9 @@ def from_pretrained(cls, pretrained_model_name_or_path, *init_inputs, **kwargs):
                             logger.info("Didn't find file {}. We won't load it.".format(full_file_name))
                             full_file_name = None
                     else:
-                        full_file_name = hf_bucket_url(pretrained_model_name_or_path, filename=file_name, mirror=None)
+                        full_file_name = hf_bucket_url(
+                            pretrained_model_name_or_path, filename=file_name, revision=revision, mirror=None
+                        )
 
                     vocab_files[file_id] = full_file_name