Update app.py (#1)

- Update app.py (ca00bce8e8d9b3db4113f3c8d6d41c5b647ec187)


Co-authored-by: Steven Liu <stevhliu@users.noreply.huggingface.co>

app.py

@@ -23,12 +23,12 @@ def _get_demo_code(path: str) -> str:
 DEMO_EXPLANATION = """
 <h1 style='text-align: center; margin-bottom: 1rem'> How to persist data from a Space to a Dataset? </h1>
 
-This demo shows how to leverage both `gradio` and `huggingface_hub` to save data from a Space to a Dataset on the Hub.
+This demo shows how to leverage `gradio` and `huggingface_hub` to save data from a Space to a Dataset on the Hub.
 When doing so, a few things must be taken care of: file formats, concurrent writes, name collision, number of commits,
-number of files,... The tabs below shows different ways of implementing a "save to dataset" feature. Depending on the
+number of files, and more. The tabs below show different ways of implementing a "save to dataset" feature. Depending on the
 complexity and usage of your app, you might want to use one or the other.
 
-This Space comes as a demo for this `huggingface_hub` guide: https://huggingface.co/docs/huggingface_hub/main/en/guides/upload#scheduled-uploads. Please check it out if you need more technical details.
+This Space comes as a demo for this `huggingface_hub` [guide](https://huggingface.co/docs/huggingface_hub/main/en/guides/upload#scheduled-uploads). Please check it out if you need more technical details.
 """
 
 JSON_DEMO_EXPLANATION = """
@@ -47,7 +47,7 @@ Works with concurrent users and replicas.
 
 ## Limitations
 
-if you expect millions of lines, you will need to split the local JSON file into multiple files to avoid getting your file tracked as LFS (5MB) on the Hub.
+If you expect millions of lines, you must split the local JSON file into multiple files to avoid getting your file tracked as LFS (5MB) on the Hub.
 
 ## Demo
 """
@@ -55,7 +55,7 @@ if you expect millions of lines, you will need to split the local JSON file into
 IMAGE_DEMO_EXPLANATION = """
 ## Use case
 
-Save images with metadata (caption, parameters, datetime,...).
+Save images with metadata (caption, parameters, datetime, etc.).
 
 ## Robustness
 
@@ -63,8 +63,8 @@ Works with concurrent users and replicas.
 
 ## Limitations
 
-  - only 10k images/folder supported on the Hub. If you expect more usage, you must save data in subfolders.
-  - only 1M images/repo supported on the Hub. If you expect more usage, you can zip your data before upload. See the _1M images Dataset_ demo.
+  - only 10k images/folder are supported on the Hub. If you expect more usage, you must save data in subfolders.
+  - only 1M images/repo supported on the Hub. If you expect more usage, you can zip your data before uploading. See the _1M images Dataset_ demo.
 
 ## Demo
 """
@@ -72,7 +72,7 @@ Works with concurrent users and replicas.
 IMAGE_1M_DEMO_EXPLANATION = """
 ## Use case:
 
-Same as _Image Dataset_ example, but with very high usage expected.
+Save 1M images with metadata (caption, parameters, datetime, etc.).
 
 ## Robustness