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04-prompt-engineering-fundamentals/README.md

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@@ -36,7 +36,7 @@ The Jupyter Notebook accompanying this lesson provides a _sandbox_ environment w
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1. **An Azure OpenAI API key** - the service endpoint for a deployed LLM.
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2. **A Python Runtime** - in which the Notebook can be executed.
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3. **Local Env Variables** - _complete the [SETUP](./../00-course-setup/SETUP.md?WT.mc_id=academic-105485-koreyst) steps now to get ready_.
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3. **Local Env Variables** - _complete the [SETUP](./../00-course-setup/02-setup-local.md?WT.mc_id=academic-105485-koreyst) steps now to get ready_.
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The notebook comes with _starter_ exercises - but you are encouraged to add your own _Markdown_ (description) and _Code_ (prompt requests) sections to try out more examples or ideas - and build your intuition for prompt design.
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18-fine-tuning/python/openai/oai-assignment.ipynb

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"Upload the data using the Files API [as described here](https://platform.openai.com/docs/guides/fine-tuning/upload-a-training-file). Note that in order to run this code, you must have done the following steps first:\n",
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" - Installed the `openai` Python package (make sure you use a version >=0.28.0 for latest features)\n",
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" - Set the `OPENAI_API_KEY` environment variable to your OpenAI API key\n",
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"To learn more, see the [Setup guide](./../../../00-course-setup/SETUP.md?WT.mc_id=academic-105485-koreyst) provided for the course.\n",
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"To learn more, see the [Setup guide](./../../../00-course-setup/02-setup-local.md?WT.mc_id=academic-105485-koreyst) provided for the course.\n",
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"\n",
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"Now, run the code to create a file for upload from your local JSONL file."
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