Fixed llm docs. (#520)

Author: lu-ohai

.github/workflows/run-unittests-default_setup.yml

@@ -2,12 +2,10 @@ name: "[Py3.8][Py3.9][Py3.10] tests/unitary/default_setup/**"
 
 on:
   workflow_dispatch:
+  push:
   pull_request:
-    paths:
-      - "ads/**"
-      - pyproject.toml
-      - "**requirements.txt"
-      - ".github/workflows/run-unittests*.yml"
+    types: [opened, reopened]
+    branches: [ "main" ]
 
 # Cancel in progress workflows on pull_requests.
 # https://docs.github.com/en/actions/using-jobs/using-concurrency#example-using-a-fallback-value

.github/workflows/run-unittests-py38-cov-report.yml

@@ -2,12 +2,10 @@ name: "[Py3.8][COV REPORT] tests/unitary/**"
 
 on:
   workflow_dispatch:
+  push:
   pull_request:
-    paths:
-      - "ads/**"
-      - pyproject.toml
-      - "**requirements.txt"
-      - ".github/workflows/run-unittests*.yml"
+    types: [opened, reopened]
+    branches: [ "main" ]
 
 # Cancel in progress workflows on pull_requests.
 # https://docs.github.com/en/actions/using-jobs/using-concurrency#example-using-a-fallback-value
@@ -116,7 +114,7 @@ jobs:
     runs-on: ubuntu-latest
     continue-on-error: true
     needs: test
-    if: ${{ success() }} && && github.event_name == 'pull_request'
+    if: ${{ success() }} && github.event_name == 'pull_request'
     env:
       COMPARE_BRANCH: main
 
@@ -155,7 +153,6 @@ jobs:
           fi
 
       - name: "Calculate coverage diff"
-        if: always()
         run: |
           set -x # print commands that are executed
 
@@ -186,7 +183,7 @@ jobs:
 
       - name: "Add comment with cov diff to PR"
         uses: actions/github-script@v6
-        if: always()
+        if: github.event_name == 'pull_request'
         with:
           github-token: ${{ github.token }}
           script: |

.github/workflows/run-unittests-py39-py310.yml

@@ -2,12 +2,10 @@ name: "[Py3.9][Py3.10] - tests/unitary/**"
 
 on:
   workflow_dispatch:
+  push:
   pull_request:
-    paths:
-      - "ads/**"
-      - pyproject.toml
-      - "**requirements.txt"
-      - ".github/workflows/run-unittests*.yml"
+    types: [opened, reopened]
+    branches: [ "main" ]
 
 # Cancel in progress workflows on pull_requests.
 # https://docs.github.com/en/actions/using-jobs/using-concurrency#example-using-a-fallback-value

docs/source/user_guide/_template/distributed_training_policies.rst

@@ -0,0 +1,7 @@
+.. admonition:: Distributed Training with OCI Data Science
+  :class: note
+
+  You need to configure your `networking <https://docs.oracle.com/en-us/iaas/Content/Network/Concepts/overview.htm>`_
+  and `IAM <https://docs.oracle.com/en-us/iaas/Content/Identity/Concepts/overview.htm>`_ policies.
+  We recommend running the training on a private subnet.
+  In this example, internet access is needed to download the source code and the pre-trained model.

docs/source/user_guide/jobs/tabs/run_job.rst

@@ -13,7 +13,7 @@ To create and start running the job:
     run.watch()
 
   .. code-tab:: bash
-    :caption: YAML
+    :caption: CLI
 
     # Use the following command to start the job run
     ads opctl run -f your_job.yaml

docs/source/user_guide/large_language_model/training_llm.rst

@@ -7,15 +7,9 @@ Oracle Cloud Infrastructure (OCI) `Data Science Jobs (Jobs) <https://docs.oracle
 provides fully managed infrastructure to enable training large language model at scale.
 This page shows an example of fine-tuning the `Llama 2 <https://ai.meta.com/llama/>`_ model. For model details on the APIs, see :doc:`../jobs/run_pytorch_ddp`.
 
-.. admonition:: Distributed Training with OCI Data Science
-  :class: note
+.. include:: ../_template/distributed_training_policies.rst
 
-  You need to configure your `networking <https://docs.oracle.com/en-us/iaas/Content/Network/Concepts/overview.htm>`_
-  and `IAM <https://docs.oracle.com/en-us/iaas/Content/Identity/Concepts/overview.htm>`_ policies.
-  We recommend running the training on a private subnet.
-  In this example, internet access is needed to download the source code and the pre-trained model.
-
-The `llama-recipes <llama-recipes>`_ repository contains example code to fine-tune llama2 model.
+The `llama-recipes <https://github.com/facebookresearch/llama-recipes>`_ repository contains example code to fine-tune llama2 model.
 The example `fine-tuning script <https://github.com/facebookresearch/llama-recipes/blob/1aecd00924738239f8d86f342b36bacad180d2b3/examples/finetuning.py>`_ supports both full parameter fine-tuning
 and `Parameter-Efficient Fine-Tuning (PEFT) <https://huggingface.co/blog/peft>`_.
 With ADS, you can start the training job by taking the source code directly from Github with no code change.