๐ Exciting News! ๐ Notebook used in the video: https://github.com/yiqiao-yin/WYNAssociates/blob/main/docs/ref-deeplearning/ex24f%20-%20what%20to%20do%20when%20rag%20system%20hallucinates.ipynb I've just released a brand-new video walkthrough ๐น that dives deep into how we can tackle hallucination issues in Retriever-Augmented Generation (RAG) systems. ๐ง ๐ก In this video, I explore a powerful solution using the `db.similarity_search_with_score` function to enhance the accuracy and reliability of our RAG system. This method is not just a band-aid but a strategic approach to significantly improve the system's performance by grounding its responses in verified information. ๐๐ ๐ What's inside the video? - A high-level overview of querying a database for document similarity. ๐️ - Step-by-step walkthrough on formatting results into a readable format and exporting them for further analysis. ๐ - Insightful tips on reducing system hallucination and enhancing response quality. ๐ - A live demonstration of the process, from query to CSV export. ๐ฅ️ Whether you're a data scientist, NLP practitioner, or just passionate about AI, this walkthrough provides valuable insights and practical steps to address one of the most pressing challenges in AI development today. ๐ Don't miss out on unlocking the full potential of your RAG systems. Check out the video, arm yourself with knowledge, and take a step towards more reliable AI solutions. ๐๐จ๐ป #AIDevelopment #MachineLearning #NaturalLanguageProcessing #DataScience #TechInnovation #aichallenges Previous 3-part videos are below: Video 1 - "Process Your Own PDF Doc into LLM Finetune-Ready Format" ๐✨ https://youtu.be/hr2kSC1evQM Unleash the magic within PDFs! Transform them from static pages into fine-tune ready formats. Our first video reveals the sorcery needed to turn chaos into streamlined, AI-friendly data. Get ready to wield your digital wand and make those PDFs dance to your tune. It's not just a tutorial; it's a transformation spectacle! ๐ฉ๐ฎ ๐ปhttps://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 Video 2 - "Fine-tune Llama2-7b LLM Using Custom Data" ๐๐ง https://youtu.be/tDkY2gpvylE Prepare your aprons for an AI flavor explosion! Video two guides you through customizing the Llama-2 model with your special ingredient—your data. This isn't just fine-tuning; it's creating a gourmet AI dish that tastes uniquely yours. Mix, bake, and savor your creation. Let's cook up some genius together! ๐ณ๐ฅ ๐ปhttps://github.com/yiqiao-yin/WYNAssociates/blob/main/docs/ref-deeplearning/ex24f%20-%20fine%20tune%20Llama%202%20using%20ysa%20data%20in%20colab.ipynb Video 3 - "Deploy Inference Endpoint on HuggingFace!" ๐๐ https://youtu.be/382yy-mCeCA Ever wanted to share your AI with the world? Video three is your ticket to stardom. Discover how to deploy your model on HuggingFace, making it as accessible as launching a rocket into space. Turn your AI project into a universal sensation. It's not just deployment; it's an interstellar journey for your model. ๐๐ฐ ๐ปhttps://github.com/yiqiao-yin/WYNAssociates/blob/main/docs/ref-deeplearning/ex24f%20-%20inference%20endpoint%20interaction%20from%20huggingface.ipynb ๐ปhttps://huggingface.co/spaces/eagle0504/streamlit-demo
Recommended gear for this workflow
- Deep Learning (Adaptive Computation and Machine Learning series) — Structured books beat scattered tutorials when you are building fundamentals.
- Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow — Structured books beat scattered tutorials when you are building fundamentals.
- Pattern Recognition and Machine Learning (Information Science and Statistics) — Structured books beat scattered tutorials when you are building fundamentals.
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