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Update app.py
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app.py
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@@ -52,39 +52,35 @@ st.sidebar.write("---")
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st.sidebar.markdown("Yiqiao Yin: [Site](https://www.y-yin.io/) | [LinkedIn](https://www.linkedin.com/in/yiqiaoyin/)")
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with st.expander("More Detailed Tutorials"):
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st.sidebar.markdown(
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r"""
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This playlist has many interesting content. Most importantly, we released coaching materials that consists of a 3-part video series that guides you through the fascinating world of Data Science, Machine Learning, and Artificial Intelligence.
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## Video Series Overview
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### Video 1: Process Your Own PDF Doc into LLM Finetune-Ready Format
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Learn how to transform PDF documents into AI model fine-tuning ready formats. This video will take you through the steps to make your PDF data AI-ready.
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- [Watch Video](https://youtu.be/hr2kSC1evQM)
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- [Tutorial Notebook](https://github.com/yiqiao-yin/WYNAssociates/blob/main/docs/ref-deeplearning/ex24f%20-%20process%20custom%20data%20from%20pdf%20and%20push%20to%20huggingface%20to%20prep%20for%20fine%20tune%20task%20of%20llama%202%20using%20lora.ipynb)
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### Video 2: Fine-tune Llama2-7b LLM Using Custom Data
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Dive into customizing the Llama-2 model with your unique dataset. This installment turns your data into a bespoke AI model.
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- [Watch Video](https://youtu.be/tDkY2gpvylE)
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- [Guide to Fine-Tuning](https://github.com/yiqiao-yin/WYNAssociates/blob/main/docs/ref-deeplearning/ex24f%20-%20fine%20tune%20Llama%202%20using%20ysa%20data%20in%20colab.ipynb)
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### Video 3: Deploy Inference Endpoint on HuggingFace!
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Discover how to make your AI model accessible to the world by deploying it on HuggingFace. This video turns your project into a global phenomenon.
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- [Watch Video](https://youtu.be/382yy-mCeCA)
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- [Deployment Guide](https://github.com/yiqiao-yin/WYNAssociates/blob/main/docs/ref-deeplearning/ex24f%20-%20inference%20endpoint%20interaction%20from%20huggingface.ipynb)
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- [HuggingFace Space](https://huggingface.co/spaces/eagle0504/streamlit-demo)
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Join us on this journey to transform static data into dynamic AI models, from data preparation and model fine-tuning to global deployment.
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"""
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st.sidebar.markdown("Yiqiao Yin: [Site](https://www.y-yin.io/) | [LinkedIn](https://www.linkedin.com/in/yiqiaoyin/)")
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with st.sidebar.expander("More Detailed Tutorials"):
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st.sidebar.markdown(
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r"""
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To fine-tune LLM such as Llama2 on custom data, please use the following tutorials as resources. For the options above such as `Llama2 on YSA` and `Llama2 on BRK Letters`, they are developed based on the content of the following videos.
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## Video Series Overview
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### Video 1: Process Your Own PDF Doc into LLM Finetune-Ready Format
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Learn how to transform PDF documents into AI model fine-tuning ready formats. This video will take you through the steps to make your PDF data AI-ready.
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- [Watch Video](https://youtu.be/hr2kSC1evQM)
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- [Tutorial Notebook](https://github.com/yiqiao-yin/WYNAssociates/blob/main/docs/ref-deeplearning/ex24f%20-%20process%20custom%20data%20from%20pdf%20and%20push%20to%20huggingface%20to%20prep%20for%20fine%20tune%20task%20of%20llama%202%20using%20lora.ipynb)
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### Video 2: Fine-tune Llama2-7b LLM Using Custom Data
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Dive into customizing the Llama-2 model with your unique dataset. This installment turns your data into a bespoke AI model.
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- [Watch Video](https://youtu.be/tDkY2gpvylE)
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- [Guide to Fine-Tuning](https://github.com/yiqiao-yin/WYNAssociates/blob/main/docs/ref-deeplearning/ex24f%20-%20fine%20tune%20Llama%202%20using%20ysa%20data%20in%20colab.ipynb)
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### Video 3: Deploy Inference Endpoint on HuggingFace!
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Discover how to make your AI model accessible to the world by deploying it on HuggingFace. This video turns your project into a global phenomenon.
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- [Watch Video](https://youtu.be/382yy-mCeCA)
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- [Deployment Guide](https://github.com/yiqiao-yin/WYNAssociates/blob/main/docs/ref-deeplearning/ex24f%20-%20inference%20endpoint%20interaction%20from%20huggingface.ipynb)
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- [HuggingFace Space](https://huggingface.co/spaces/eagle0504/streamlit-demo)
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"""
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)
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