[Doc]: fix various typos in different files (#3497)

Author: didier-durand

docs/README.md

@@ -43,7 +43,7 @@ check how they look before committing for instance). You don't have to commit th
 
 ## Building the documentation
 
-Once you have setup the `doc-builder` and additional packages with the pip install command above,
+Once you have set up the `doc-builder` and additional packages with the pip install command above,
 you can generate the documentation by typing the following command:
 
 ```bash

docs/source/en/guides/inference.md

@@ -152,7 +152,7 @@ You can use [`InferenceClient`] to run chat completion with local inference serv
 ```
 
 > [!TIP]
-> Similarily to the OpenAI Python client, [`InferenceClient`] can be used to run Chat Completion inference with any OpenAI REST API-compatible endpoint.
+> Similarly to the OpenAI Python client, [`InferenceClient`] can be used to run Chat Completion inference with any OpenAI REST API-compatible endpoint.
 
 ### Authentication
 

docs/source/en/quick-start.md

@@ -75,7 +75,7 @@ hf auth login
 
 The command will tell you if you are already logged in and prompt you for your token. The token is then validated and saved in your `HF_HOME` directory (defaults to `~/.cache/huggingface/token`). Any script or library interacting with the Hub will use this token when sending requests.
 
-Alternatively, you can programmatically login using [`login`] in a notebook or a script:
+Alternatively, you can programmatically log in using [`login`] in a notebook or a script:
 
 ```py
 >>> from huggingface_hub import login

src/huggingface_hub/README.md

@@ -73,7 +73,7 @@ to the Hub: https://huggingface.co/docs/hub/adding-a-model.
 
 ### API utilities in `hf_api.py`
 
-You don't need them for the standard publishing workflow (ie. using git command line), however, if you need a
+You don't need them for the standard publishing workflow (i.e. using git command line), however, if you need a
 programmatic way of creating a repo, deleting it (`⚠️ caution`), pushing a
 single file to a repo or listing models from the Hub, you'll find helpers in
 `hf_api.py`. Some example functionality available with the `HfApi` class:

src/huggingface_hub/_inference_endpoints.py

@@ -329,7 +329,7 @@ def pause(self) -> "InferenceEndpoint":
         """Pause the Inference Endpoint.
 
         A paused Inference Endpoint will not be charged. It can be resumed at any time using [`InferenceEndpoint.resume`].
-        This is different than scaling the Inference Endpoint to zero with [`InferenceEndpoint.scale_to_zero`], which
+        This is different from scaling the Inference Endpoint to zero with [`InferenceEndpoint.scale_to_zero`], which
         would be automatically restarted when a request is made to it.
 
         This is an alias for [`HfApi.pause_inference_endpoint`]. The current object is mutated in place with the
@@ -367,7 +367,7 @@ def resume(self, running_ok: bool = True) -> "InferenceEndpoint":
     def scale_to_zero(self) -> "InferenceEndpoint":
         """Scale Inference Endpoint to zero.
 
-        An Inference Endpoint scaled to zero will not be charged. It will be resume on the next request to it, with a
+        An Inference Endpoint scaled to zero will not be charged. It will be resumed on the next request to it, with a
         cold start delay. This is different than pausing the Inference Endpoint with [`InferenceEndpoint.pause`], which
         would require a manual resume with [`InferenceEndpoint.resume`].
 

src/huggingface_hub/_local_folder.py

@@ -206,7 +206,7 @@ def get_local_download_paths(local_dir: Path, filename: str) -> LocalDownloadFil
         [`LocalDownloadFilePaths`]: the paths to the files (file_path, lock_path, metadata_path, incomplete_path).
     """
     # filename is the path in the Hub repository (separated by '/')
-    # make sure to have a cross platform transcription
+    # make sure to have a cross-platform transcription
     sanitized_filename = os.path.join(*filename.split("/"))
     if os.name == "nt":
         if sanitized_filename.startswith("..\\") or "\\..\\" in sanitized_filename:
@@ -246,7 +246,7 @@ def get_local_upload_paths(local_dir: Path, filename: str) -> LocalUploadFilePat
         [`LocalUploadFilePaths`]: the paths to the files (file_path, lock_path, metadata_path).
     """
     # filename is the path in the Hub repository (separated by '/')
-    # make sure to have a cross platform transcription
+    # make sure to have a cross-platform transcription
     sanitized_filename = os.path.join(*filename.split("/"))
     if os.name == "nt":
         if sanitized_filename.startswith("..\\") or "\\..\\" in sanitized_filename:

src/huggingface_hub/cli/_cli_utils.py

@@ -50,7 +50,7 @@ class AlphabeticalMixedGroup(typer.core.TyperGroup):
     """
 
     def list_commands(self, ctx: click.Context) -> list[str]:  # type: ignore[name-defined]
-        # click.Group stores both commands and sub-groups in `self.commands`
+        # click.Group stores both commands and subgroups in `self.commands`
         return sorted(self.commands.keys())
 
 

src/huggingface_hub/inference/_client.py

@@ -190,7 +190,7 @@ def __init__(
             )
         token = token if token is not None else api_key
         if isinstance(token, bool):
-            # Legacy behavior: previously is was possible to pass `token=False` to disable authentication. This is not
+            # Legacy behavior: previously it was possible to pass `token=False` to disable authentication. This is not
             # supported anymore as authentication is required. Better to explicitly raise here rather than risking
             # sending the locally saved token without the user knowing about it.
             if token is False:
@@ -859,7 +859,7 @@ def chat_completion(
         >>> messages = [
         ...     {
         ...         "role": "user",
-        ...         "content": "I saw a puppy a cat and a raccoon during my bike ride in the park. What did I saw and when?",
+        ...         "content": "I saw a puppy a cat and a raccoon during my bike ride in the park. What did I see and when?",
         ...     },
         ... ]
         >>> response_format = {
@@ -1427,7 +1427,7 @@ def image_to_text(self, image: ContentT, *, model: Optional[str] = None) -> Imag
         Takes an input image and return text.
 
         Models can have very different outputs depending on your use case (image captioning, optical character recognition
-        (OCR), Pix2Struct, etc). Please have a look to the model card to learn more about a model's specificities.
+        (OCR), Pix2Struct, etc.). Please have a look to the model card to learn more about a model's specificities.
 
         Args:
             image (`Union[str, Path, bytes, BinaryIO, PIL.Image.Image]`):

src/huggingface_hub/inference/_common.py

@@ -364,7 +364,7 @@ async def _async_yield_from(client: httpx.AsyncClient, response: httpx.Response)
 #
 # Both approaches have very similar APIs, but not exactly the same. What we do first in
 # the `text_generation` method is to assume the model is served via TGI. If we realize
-# it's not the case (i.e. we receive an HTTP 400 Bad Request), we fallback to the
+# it's not the case (i.e. we receive an HTTP 400 Bad Request), we fall back to the
 # default API with a warning message. When that's the case, We remember the unsupported
 # attributes for this model in the `_UNSUPPORTED_TEXT_GENERATION_KWARGS` global variable.
 #

src/huggingface_hub/inference/_generated/_async_client.py

@@ -181,7 +181,7 @@ def __init__(
             )
         token = token if token is not None else api_key
         if isinstance(token, bool):
-            # Legacy behavior: previously is was possible to pass `token=False` to disable authentication. This is not
+            # Legacy behavior: previously it was possible to pass `token=False` to disable authentication. This is not
             # supported anymore as authentication is required. Better to explicitly raise here rather than risking
             # sending the locally saved token without the user knowing about it.
             if token is False:
@@ -885,7 +885,7 @@ async def chat_completion(
         >>> messages = [
         ...     {
         ...         "role": "user",
-        ...         "content": "I saw a puppy a cat and a raccoon during my bike ride in the park. What did I saw and when?",
+        ...         "content": "I saw a puppy a cat and a raccoon during my bike ride in the park. What did I see and when?",
         ...     },
         ... ]
         >>> response_format = {
@@ -1460,7 +1460,7 @@ async def image_to_text(self, image: ContentT, *, model: Optional[str] = None) -
         Takes an input image and return text.
 
         Models can have very different outputs depending on your use case (image captioning, optical character recognition
-        (OCR), Pix2Struct, etc). Please have a look to the model card to learn more about a model's specificities.
+        (OCR), Pix2Struct, etc.). Please have a look to the model card to learn more about a model's specificities.
 
         Args:
             image (`Union[str, Path, bytes, BinaryIO, PIL.Image.Image]`):