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Fixed punctuation in caching.md
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This file had inconsistent use of the colon marker when referring to code. Some sentences ended with the colon (":") while others had no punctuation mark.

 - Added a colon after "add a line like the following to ~/.bashrc"
 - Added a colon after "downloading the models locally with"
 - Added a colon after “cache location with code like”

So now the file is consistent with lines that end like:

 - “through the Colab host:”
 - “workarounds for this situation:”
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jmarcinowski authored Apr 5, 2024
1 parent ec3a1b3 commit c8ad7a4
Showing 1 changed file with 4 additions and 4 deletions.
8 changes: 4 additions & 4 deletions site/en/hub/caching.md
Original file line number Diff line number Diff line change
Expand Up @@ -29,7 +29,7 @@ location `/tmp/tfhub_modules` (or whatever `os.path.join(tempfile.gettempdir(),
Users who prefer persistent caching across system reboots can instead set
`TFHUB_CACHE_DIR` to a location in their home directory. For example, a user of
the bash shell on a Linux system can add a line like the following to
`~/.bashrc`
`~/.bashrc`:

```bash
export TFHUB_CACHE_DIR=$HOME/.cache/tfhub_modules
Expand All @@ -41,7 +41,7 @@ persistent location, be aware that there is no automatic cleanup.
### Reading from remote storage

Users can instruct the `tensorflow_hub` library to directly read models from
remote storage (GCS) instead of downloading the models locally with
remote storage (GCS) instead of downloading the models locally with:

```shell
os.environ["TFHUB_MODEL_LOAD_FORMAT"] = "UNCOMPRESSED"
Expand All @@ -64,7 +64,7 @@ location by default. There are two workarounds for this situation:
The easiest solution is to instruct the `tensorflow_hub` library to read the
models from TF Hub's GCS bucket as explained above. Users with their own GCS
bucket can instead specify a directory in their bucket as the cache location
with code like
with code like:

```python
import os
Expand All @@ -83,4 +83,4 @@ load_options =
tf.saved_model.LoadOptions(experimental_io_device='/job:localhost')
reloaded_model = hub.load("https://tfhub.dev/...", options=load_options)
```
**Note:** See more information regarding valid handles [here](tf2_saved_model.md#model_handles).
**Note:** See more information regarding valid handles [here](tf2_saved_model.md#model_handles).

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