Model versioning

model_cards/t5-11b-README.md

@@ -12,8 +12,8 @@ inference: false
 
 ## Disclaimer
 
-Due do it's immense size, `t5-11b` requires some special treatment. 
-First, `t5-11b` should be loaded with flag `use_cdn` set to `False` as follows:
+**Before `transformers` v3.5.0**, due do its immense size, `t5-11b` required some special treatment. 
+If you're using transformers `<= v3.4.0`, `t5-11b` should be loaded with flag `use_cdn` set to `False` as follows:
 
 ```python
 t5 = transformers.T5ForConditionalGeneration.from_pretrained('t5-11b', use_cdn = False)

scripts/fsmt/convert-allenai-wmt16.sh

@@ -56,7 +56,3 @@ cd -
 perl -le 'for $f (@ARGV) { print qq[transformers-cli upload -y $_/$f --filename $_/$f] for ("wmt16-en-de-dist-12-1", "wmt16-en-de-dist-6-1", "wmt16-en-de-12-1")}' vocab-src.json vocab-tgt.json tokenizer_config.json config.json
 # add/remove files as needed
 
-# Caching note: Unfortunately due to CDN caching the uploaded model may be unavailable for up to 24hs after upload
-# So the only way to start using the new model sooner is either:
-# 1. download it to a local path and use that path as model_name
-# 2. make sure you use: from_pretrained(..., use_cdn=False) everywhere

scripts/fsmt/convert-allenai-wmt19.sh

@@ -44,7 +44,3 @@ cd -
 perl -le 'for $f (@ARGV) { print qq[transformers-cli upload -y $_/$f --filename $_/$f] for ("wmt19-de-en-6-6-base", "wmt19-de-en-6-6-big")}' vocab-src.json vocab-tgt.json tokenizer_config.json config.json
 # add/remove files as needed
 
-# Caching note: Unfortunately due to CDN caching the uploaded model may be unavailable for up to 24hs after upload
-# So the only way to start using the new model sooner is either:
-# 1. download it to a local path and use that path as model_name
-# 2. make sure you use: from_pretrained(..., use_cdn=False) everywhere

scripts/fsmt/convert-facebook-wmt19.sh

@@ -55,7 +55,3 @@ cd -
 perl -le 'for $f (@ARGV) { print qq[transformers-cli upload -y $_/$f --filename $_/$f] for map { "wmt19-$_" } ("en-ru", "ru-en", "de-en", "en-de")}' vocab-src.json vocab-tgt.json tokenizer_config.json config.json
 # add/remove files as needed
 
-# Caching note: Unfortunately due to CDN caching the uploaded model may be unavailable for up to 24hs after upload
-# So the only way to start using the new model sooner is either:
-# 1. download it to a local path and use that path as model_name
-# 2. make sure you use: from_pretrained(..., use_cdn=False) everywhere

src/transformers/commands/user.py

@@ -1,4 +1,5 @@
 import os
+import subprocess
 import sys
 from argparse import ArgumentParser
 from getpass import getpass
@@ -21,8 +22,10 @@ def register_subcommand(parser: ArgumentParser):
         whoami_parser.set_defaults(func=lambda args: WhoamiCommand(args))
         logout_parser = parser.add_parser("logout", help="Log out")
         logout_parser.set_defaults(func=lambda args: LogoutCommand(args))
-        # s3
-        s3_parser = parser.add_parser("s3", help="{ls, rm} Commands to interact with the files you upload on S3.")
+        # s3_datasets (s3-based system)
+        s3_parser = parser.add_parser(
+            "s3_datasets", help="{ls, rm} Commands to interact with the files you upload on S3."
+        )
         s3_subparsers = s3_parser.add_subparsers(help="s3 related commands")
         ls_parser = s3_subparsers.add_parser("ls")
         ls_parser.add_argument("--organization", type=str, help="Optional: organization namespace.")
@@ -31,17 +34,42 @@ def register_subcommand(parser: ArgumentParser):
         rm_parser.add_argument("filename", type=str, help="individual object filename to delete from S3.")
         rm_parser.add_argument("--organization", type=str, help="Optional: organization namespace.")
         rm_parser.set_defaults(func=lambda args: DeleteObjCommand(args))
-        # upload
-        upload_parser = parser.add_parser("upload", help="Upload a model to S3.")
-        upload_parser.add_argument(
-            "path", type=str, help="Local path of the model folder or individual file to upload."
-        )
+        upload_parser = s3_subparsers.add_parser("upload", help="Upload a file to S3.")
+        upload_parser.add_argument("path", type=str, help="Local path of the folder or individual file to upload.")
         upload_parser.add_argument("--organization", type=str, help="Optional: organization namespace.")
         upload_parser.add_argument(
             "--filename", type=str, default=None, help="Optional: override individual object filename on S3."
         )
         upload_parser.add_argument("-y", "--yes", action="store_true", help="Optional: answer Yes to the prompt")
         upload_parser.set_defaults(func=lambda args: UploadCommand(args))
+        # deprecated model upload
+        upload_parser = parser.add_parser(
+            "upload",
+            help=(
+                "Deprecated: used to be the way to upload a model to S3."
+                " We now use a git-based system for storing models and other artifacts."
+                " Use the `repo create` command instead."
+            ),
+        )
+        upload_parser.set_defaults(func=lambda args: DeprecatedUploadCommand(args))
+
+        # new system: git-based repo system
+        repo_parser = parser.add_parser(
+            "repo", help="{create, ls-files} Commands to interact with your huggingface.co repos."
+        )
+        repo_subparsers = repo_parser.add_subparsers(help="huggingface.co repos related commands")
+        ls_parser = repo_subparsers.add_parser("ls-files", help="List all your files on huggingface.co")
+        ls_parser.add_argument("--organization", type=str, help="Optional: organization namespace.")
+        ls_parser.set_defaults(func=lambda args: ListReposObjsCommand(args))
+        repo_create_parser = repo_subparsers.add_parser("create", help="Create a new repo on huggingface.co")
+        repo_create_parser.add_argument(
+            "name",
+            type=str,
+            help="Name for your model's repo. Will be namespaced under your username to build the model id.",
+        )
+        repo_create_parser.add_argument("--organization", type=str, help="Optional: organization namespace.")
+        repo_create_parser.add_argument("-y", "--yes", action="store_true", help="Optional: answer Yes to the prompt")
+        repo_create_parser.set_defaults(func=lambda args: RepoCreateCommand(args))
 
 
 class ANSI:
@@ -51,6 +79,7 @@ class ANSI:
 
     _bold = "\u001b[1m"
     _red = "\u001b[31m"
+    _gray = "\u001b[90m"
     _reset = "\u001b[0m"
 
     @classmethod
@@ -61,6 +90,27 @@ def bold(cls, s):
     def red(cls, s):
         return "{}{}{}".format(cls._bold + cls._red, s, cls._reset)
 
+    @classmethod
+    def gray(cls, s):
+        return "{}{}{}".format(cls._gray, s, cls._reset)
+
+
+def tabulate(rows: List[List[Union[str, int]]], headers: List[str]) -> str:
+    """
+    Inspired by:
+
+    - stackoverflow.com/a/8356620/593036
+    - stackoverflow.com/questions/9535954/printing-lists-as-tabular-data
+    """
+    col_widths = [max(len(str(x)) for x in col) for col in zip(*rows, headers)]
+    row_format = ("{{:{}}} " * len(headers)).format(*col_widths)
+    lines = []
+    lines.append(row_format.format(*headers))
+    lines.append(row_format.format(*["-" * w for w in col_widths]))
+    for row in rows:
+        lines.append(row_format.format(*row))
+    return "\n".join(lines)
+
 
 class BaseUserCommand:
     def __init__(self, args):
@@ -124,22 +174,6 @@ def run(self):
 
 
 class ListObjsCommand(BaseUserCommand):
-    def tabulate(self, rows: List[List[Union[str, int]]], headers: List[str]) -> str:
-        """
-        Inspired by:
-
-        - stackoverflow.com/a/8356620/593036
-        - stackoverflow.com/questions/9535954/printing-lists-as-tabular-data
-        """
-        col_widths = [max(len(str(x)) for x in col) for col in zip(*rows, headers)]
-        row_format = ("{{:{}}} " * len(headers)).format(*col_widths)
-        lines = []
-        lines.append(row_format.format(*headers))
-        lines.append(row_format.format(*["-" * w for w in col_widths]))
-        for row in rows:
-            lines.append(row_format.format(*row))
-        return "\n".join(lines)
-
     def run(self):
         token = HfFolder.get_token()
         if token is None:
@@ -155,7 +189,7 @@ def run(self):
             print("No shared file yet")
             exit()
         rows = [[obj.filename, obj.LastModified, obj.ETag, obj.Size] for obj in objs]
-        print(self.tabulate(rows, headers=["Filename", "LastModified", "ETag", "Size"]))
+        print(tabulate(rows, headers=["Filename", "LastModified", "ETag", "Size"]))
 
 
 class DeleteObjCommand(BaseUserCommand):
@@ -173,6 +207,85 @@ def run(self):
         print("Done")
 
 
+class ListReposObjsCommand(BaseUserCommand):
+    def run(self):
+        token = HfFolder.get_token()
+        if token is None:
+            print("Not logged in")
+            exit(1)
+        try:
+            objs = self._api.list_repos_objs(token, organization=self.args.organization)
+        except HTTPError as e:
+            print(e)
+            print(ANSI.red(e.response.text))
+            exit(1)
+        if len(objs) == 0:
+            print("No shared file yet")
+            exit()
+        rows = [[obj.filename, obj.lastModified, obj.commit, obj.size] for obj in objs]
+        print(tabulate(rows, headers=["Filename", "LastModified", "Commit-Sha", "Size"]))
+
+
+class RepoCreateCommand(BaseUserCommand):
+    def run(self):
+        token = HfFolder.get_token()
+        if token is None:
+            print("Not logged in")
+            exit(1)
+        try:
+            stdout = subprocess.run(["git", "--version"], capture_output=True).stdout.decode("utf-8")
+            print(ANSI.gray(stdout.strip()))
+        except FileNotFoundError:
+            print("Looks like you do not have git installed, please install.")
+
+        try:
+            stdout = subprocess.run(["git-lfs", "--version"], capture_output=True).stdout.decode("utf-8")
+            print(ANSI.gray(stdout.strip()))
+        except FileNotFoundError:
+            print(
+                ANSI.red(
+                    "Looks like you do not have git-lfs installed, please install."
+                    " You can install from https://git-lfs.github.com/."
+                    " Then run `git lfs install` (you only have to do this once)."
+                )
+            )
+        print("")
+
+        user, _ = self._api.whoami(token)
+        namespace = self.args.organization if self.args.organization is not None else user
+
+        print("You are about to create {}".format(ANSI.bold(namespace + "/" + self.args.name)))
+
+        if not self.args.yes:
+            choice = input("Proceed? [Y/n] ").lower()
+            if not (choice == "" or choice == "y" or choice == "yes"):
+                print("Abort")
+                exit()
+        try:
+            url = self._api.create_repo(token, name=self.args.name, organization=self.args.organization)
+        except HTTPError as e:
+            print(e)
+            print(ANSI.red(e.response.text))
+            exit(1)
+        print("\nYour repo now lives at:")
+        print("  {}".format(ANSI.bold(url)))
+        print("\nYou can clone it locally with the command below," " and commit/push as usual.")
+        print(f"\n  git clone {url}")
+        print("")
+
+
+class DeprecatedUploadCommand(BaseUserCommand):
+    def run(self):
+        print(
+            ANSI.red(
+                "Deprecated: used to be the way to upload a model to S3."
+                " We now use a git-based system for storing models and other artifacts."
+                " Use the `repo create` command instead."
+            )
+        )
+        exit(1)
+
+
 class UploadCommand(BaseUserCommand):
     def walk_dir(self, rel_path):
         """

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.
 
@@ -362,14 +366,15 @@ def get_config_dict(cls, pretrained_model_name_or_path: str, **kwargs) -> Tuple[
         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)
 
         if os.path.isdir(pretrained_model_name_or_path):
             config_file = os.path.join(pretrained_model_name_or_path, CONFIG_NAME)
         elif os.path.isfile(pretrained_model_name_or_path) or is_remote_url(pretrained_model_name_or_path):
             config_file = pretrained_model_name_or_path
         else:
             config_file = hf_bucket_url(
-                pretrained_model_name_or_path, filename=CONFIG_NAME, use_cdn=False, mirror=None
+                pretrained_model_name_or_path, filename=CONFIG_NAME, revision=revision, mirror=None
             )
 
         try:
@@ -383,11 +388,10 @@ def get_config_dict(cls, pretrained_model_name_or_path: str, **kwargs) -> Tuple[
                 local_files_only=local_files_only,
             )
             # Load config dict
-            if resolved_config_file is None:
-                raise EnvironmentError
             config_dict = cls._dict_from_json_file(resolved_config_file)
 
-        except EnvironmentError:
+        except EnvironmentError as err:
+            logger.error(err)
             msg = (
                 f"Can't load config 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"

src/transformers/convert_fsmt_original_pytorch_checkpoint_to_pytorch.py

@@ -248,10 +248,6 @@ def convert_fsmt_checkpoint_to_pytorch(fsmt_checkpoint_path, pytorch_dump_folder
     print("\nLast step is to upload the files to s3")
     print(f"cd {data_root}")
     print(f"transformers-cli upload {model_dir}")
-    print(
-        "Note: CDN caches files for up to 24h, so either use a local model path "
-        "or use `from_pretrained(mname, use_cdn=False)` to use the non-cached version."
-    )
 
 
 if __name__ == "__main__":