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update transformers section (#1112)

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* update transformers section

Adding distilbert example, and the user does not need to install tensorflow or pytorch, but upgrade transformers library.

* Correct Sphinx syntax errors in code-blocks.

Signed-off-by: Michael Vincerra <michael.vincerra@intel.com>

Co-authored-by: Michael Vincerra <michael.vincerra@intel.com>
This commit is contained in:
Rahul
2020-04-10 17:14:01 -07:00
committed by GitHub
co-authored by Michael Vincerra
parent ef7fa72d94
commit 2f1b250cf8
1 changed files with 7 additions and 7 deletions
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source/guides/stacks/dlrs.rst
+7 -7
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@@ -531,7 +531,7 @@ To run the notebook, you will need to run the Deep Learning Reference Stack, mou
.. code-block:: bash
docker run -it -v ${PWD}:/workspace -p 8888:8888 clearlinux/stacks-dlrs-oss
docker run -it -v ${PWD}:/workspace -p 8888:8888 clearlinux/stacks-pytorch-mkl:latest
#. From within the container, navigate to the workspace, and clone the
@@ -540,21 +540,22 @@ To run the notebook, you will need to run the Deep Learning Reference Stack, mou
.. code-block:: bash
cd workspace
git clone https://github.com/huggingface/transformers.git
git clone https://gist.github.com/16d38f2c9c688963c166c000330a3c11.git
#. Navigate to the Transformers notebook directory, and start a Jupyter Notebook that is linked to the exterior port. Be sure to copy the token from the output of starting Jupyter Notebook.
#. Start a Jupyter Notebook that is linked to the exterior port.
Be sure to copy the token from the output of starting Jupyter Notebook.
.. code-block:: bash
cd transformers/notebooks
pip install jupyter --upgrade
jupyter notebook --ip 0.0.0.0 --no-browser --allow-root
#. To access the Jupyter Notebook, open a browser.
#. Return to the Terminal where you launched Jupyter Notebook. Copy one of the URLs that appears after "Or copy and paste on of these URLs."
#. Return to the Terminal where you launched Jupyter Notebook.
Copy one of the URLs that appears after "Or copy and paste on of these URLs."
#. Paste the URL (with embedded token) into the browser window.
@@ -569,7 +570,6 @@ From the browser, you will see the following notebooks.
Figure 1: Transformers Jupyter Notebooks
The first notebook, `01-training-tokenizers.ipynb` uses a relatively small dataset that makes for a quick download, and can be run with any of the DLRS v5.0 containers.
This example along with the other notebooks show how to get up and running with Transformers. More detail on using Transformers* is available through the `Transformers`_ github repository.