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Himanshu Singh
Приєднався 6 жов 2024
"Welcome to a world where data shapes the future! I’m Himanshu Singh, a Data Scientist and AI Engineer with nearly 4 years of experience across diverse industries. On this channel, I break down complex data science and AI concepts into simple, actionable insights, so you can learn, grow, and thrive in the digital age.
From cutting-edge tutorials to real-world applications, this is your go-to space for mastering all things data-completely free! Ready to unlock the power of data with me? Hit that subscribe button and join the journey toward smarter solutions and endless innovation!"
From cutting-edge tutorials to real-world applications, this is your go-to space for mastering all things data-completely free! Ready to unlock the power of data with me? Hit that subscribe button and join the journey toward smarter solutions and endless innovation!"
LLAMA 3.3 70B: Comparison between Llama 3.1 405B and Llama 3.1 70B Open Source LLM
Explore the future of AI with this in-depth comparison of Llama 3.3 70B, Llama 3.1 405B, and Llama 3.1 70B Open Source LLMs. In this video, you’ll uncover key differences and advancements, showcasing how these models push the boundaries of AI capabilities. Perfect for AI enthusiasts and professionals eager to stay ahead in the world of cutting-edge generative AI technology.
LINKS-
Nvidia Llama 3.3 NIM - build.nvidia.com/meta/llama-3_3-70b-instruct?snippet_tab=LangChain
Mentorship Form - forms.gle/oe3W9qdW6TiW6sTH7
#Llama3 #LLM #AItechnology #generativeAI #futureAI #opensource #AIbreakthroughs
Don't forget to like and subscribe for more exciting AI content!
LINKS-
Nvidia Llama 3.3 NIM - build.nvidia.com/meta/llama-3_3-70b-instruct?snippet_tab=LangChain
Mentorship Form - forms.gle/oe3W9qdW6TiW6sTH7
#Llama3 #LLM #AItechnology #generativeAI #futureAI #opensource #AIbreakthroughs
Don't forget to like and subscribe for more exciting AI content!
Переглядів: 340
Відео
Complete Code: Multi-Modal RAG with Unstructured IO & LangChain #multimodal #rag
Переглядів 1 тис.Місяць тому
Explore the future of AI with this deep dive into Multi-Modal Retrieval-Augmented Generation (RAG) using Unstructured IO and LangChain. In this video, you’ll discover how this advanced AI technology integrates multiple data modalities to enhance retrieval and response generation, setting a new standard in AI interactions. Perfect for AI enthusiasts and professionals eager to explore the next wa...
Multi-Modal RAG with Unstructured IO & LangChain #multimodal #rag
Переглядів 521Місяць тому
Explore the future of AI with this deep dive into Multi-Modal Retrieval-Augmented Generation (RAG) using Unstructured IO and LangChain. In this video, you’ll discover how this advanced AI technology integrates multiple data modalities to enhance retrieval and response generation, setting a new standard in AI interactions. Perfect for AI enthusiasts and professionals eager to explore the next wa...
VIS-RAG CODE Walkthrough in Google Colab #multimodal #googlecolab
Переглядів 143Місяць тому
Dive into the technical side of Vision-Based Multi-Modal Retrieval-Augmented Generation (VIS-RAG) with this detailed code walkthrough. In this video, we explore the implementation of VIS-RAG in Google Colab, providing hands-on guidance on how to integrate visual and textual data for smarter AI interactions. From setting up the environment to running embedding techniques and leveraging large lan...
Demo Vis-RAG : Test Vis RAG Pipeline on Hugging Face #rag #multimodal
Переглядів 140Місяць тому
Explore the future of AI with this exciting demo of the Vis-RAG pipeline on Hugging Face. In this video, you’ll discover how multimodal Retrieval-Augmented Generation (RAG) integrates vision and language models to create a seamless, intelligent system for answering queries and generating content. Perfect for AI enthusiasts and developers eager to explore advanced multimodal AI applications and ...
VIS-RAG: Complete Information about Vision Based Multi-Modal RAG #rag #multimodal
Переглядів 568Місяць тому
VIS-RAG: Complete Information about Vision-Based Multi-Modal RAG Explore the future of AI with this deep dive into Vision-Based Multi-Modal Retrieval-Augmented Generation (VIS-RAG) . Discover how this groundbreaking technology integrates visual and textual data to enable smarter, more dynamic AI interactions. From embedding techniques to large language models (LLMs) , learn how VIS-RAG is revol...
Colpali : End to End development of Streamlit based Multi-Modal RAG App
Переглядів 1,7 тис.2 місяці тому
Explore the end-to-end development of a Streamlit-based Multi-Modal Retrieval-Augmented Generation (RAG) App powered by the advanced Colpali method. In this video, we walk you through the full process of building an app that allows users to upload PDFs, ask questions, and get real-time answers using a robust language model. Discover how to set up data extraction, chunking, and encoding with Lan...
LLMs Overview | LLM API & Open Source Models | Transformers, API Costing, GPU for Open Source LLM
Переглядів 1062 місяці тому
In this video, we dive into the world of Large Language Models (LLMs) and explore the landscape of both API-based and open-source models. We'll cover the basics of Transformers, discuss API costing for LLMs, and look into how GPUs play a crucial role in running open-source LLMs efficiently. Whether you're new to LLMs or looking to deepen your understanding, this video will give you a comprehens...
Introduction to Generative AI | RAG & Fine tuning -Part II #genai #rag
Переглядів 952 місяці тому
In this video, I introduce the fascinating world of Generative AI and break down the key differences between Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), and Generative AI (GenAI). You'll also get an insightful explanation of Large Language Models (LLMs) and how they contribute to the rapid advancements in AI today. Whether you're a beginner or someone looking to exp...
Introduction to Generative AI | Generative AI Explained -Part I #genai #rag
Переглядів 1952 місяці тому
In this video, I introduce the fascinating world of Generative AI and break down the key differences between Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), and Generative AI (GenAI). You'll also get an insightful explanation of Large Language Models (LLMs) and how they contribute to the rapid advancements in AI today. Whether you're a beginner or someone looking to exp...
Colpali: Complete Code Walkthrough #genai #rag #multimodal
Переглядів 1,1 тис.3 місяці тому
Explore the future of AI with this deep dive into multimodal Retrieval-Augmented Generation (RAG) using Colpali. In this video, you’ll get a complete code walkthrough of how this cutting-edge AI technology integrates multiple data types to enhance content generation and revolutionize our interaction with AI systems. Perfect for AI enthusiasts and developers eager to learn about the next wave of...
ColPali: Efficient Document Retrieval for Multi-Modal RAG Systems #genai #multimodal #rag
Переглядів 6153 місяці тому
Explore the future of AI with this deep dive into multimodal Retrieval-Augmented Generation (RAG). In this video, you’ll learn how this cutting-edge AI technology merges different data types to enhance content generation and revolutionize the way we interact with AI. Perfect for AI enthusiasts and anyone interested in the next wave of generative AI advancements. #multimodal #multimodalAI #RAG #...
Multimodal RAG Systems: An Introduction to Multi-Modal RAG with Colpali #multimodal #rag #genai
Переглядів 1893 місяці тому
Explore the future of AI with this deep dive into multimodal Retrieval-Augmented Generation (RAG). In this video, you’ll learn how this cutting-edge AI technology merges different data types to enhance content generation and revolutionize the way we interact with AI. Perfect for AI enthusiasts and anyone interested in the next wave of generative AI advancements. #multimodal #multimodalAI #RAG #...
Have You Any Paid Course for Job Interview Preparation like mock interview something
Great explanation, thank you! However, I have a question-what if I need to store that compressed data in an LLM's knowledge ? Should it be converted into a specific format like ALPCA or something else? Additionally, how can we integrate this data into the LLM's knowledge effectively? Could you please guide me?
Thanks for your video. Is there a way to store the data in a vector database instead of uploading the files every time?
So , did u pay for using open ai API??
@@uknowme4_5 yes I paid for it.
hi himanshu i have one doubt how llama 3.3 costing has 0.1$ for 1m tokken . do we need to api to call it's that price or we download the model to local and we infrence it to 1m token then the total cost of hardware consuption and electricty. its that price i am confused
its the total tokens, prompt + response. and the cost is only on api
Thank you so much for this amazing video! Could you help me with something unrelated: My OKX wallet holds some USDT, and I have the seed phrase. (alarm fetch churn bridge exercise tape speak race clerk couch crater letter). Could you explain how to move them to Binance?
I truly love your channel. Keep doing the best work. 😊
Thank you so much 😀
Original Video: ua-cam.com/video/uLrReyH5cu0/v-deo.html
Great work. Thanks
Glad you liked it!😊
great work. very nicely explained.
Glad it was helpful!😊
Hospitals have a use case where various types of documents need to be sifted g or a particular patient's medical imaging, reports, prescriptions, labs, referrals in between practices, billing, insurance claims, hand written notes by doctors, nurses etc. The idea is to extract relevant information about the patients prescribed treatment at the hospital during the stay of the patient and compare it to established standards of care giving in order to find discrepancies. Can colpali rag model be applicable in this given scenario?
Great work. Thank.
What is the Hardware requirements you use for running this solution. I can see Llama 3.2 11B model requires significant GPU memory.
Great! . Subscribed
Thanks for the sub!
Awesome ❤
Thank you
How is the performance compared to ColPali?
hi Himanshu can you please give me requirements.txt file. Im getting lot of error while doing it in vs code
Hi Prashanth, Can you refer to my ua-cam.com/video/JKNii9rIdmU/v-deo.htmlsi=inS2BIQauEuV2VBQ this video as Colpali need some system level packages and I have explained it in this video. Thanks
Hi Himanshu, it good to see that you are exploring the things which normal youtubes channel is not covering. Just wanted to know about the application, that when i am loading the 2MB file for my 8GB RAM, system it is taking 15 min to upload the file only, can you help me on that, what do i need to do.
@@VikashKumar-ty6uy Yes, It will take as colpali model itself needs GPU for to run smoothly. You can try on google colab which is providing T4 gpus in free version
I got an idea about colpali completely, I was researching a lot about image based query analyzer.. Your video helped me out. Thanks a lot ❤
Can anyone please assist how this thing can be achieved using FASTAPI?
Will try to create separate video on it.
Hi Himanshu. Are you using paid version for app key
@@swatidutta2978 I am Using GPT4-o multi model api key which is paid.
Bro, you are really good.
Thanks 😅
Use case is to extract the relevant text along with images available in the pdf using generative ai, When any prompt is given then relevant text and images should display as response as such as in pdf in a order, (not images separate text separate).Dont need full page itself containing irrelevant answers also
good one. eagerly waiting for next one of streamlit end to end app
Thank you! The video is live now you can find it out on the Multi-Modal Playlist.
Make an in-depth video on Transformer as it is the base of all LLMs
Thanks for the suggestion I will upload it very soon.
What tool are you using for presenting?? Btw just came across your channel and am loving it so far ❤ Here's a request - Keep uploading daily 🙌 Explore the basics first because I found your first 3 videos too technical 😅 I'm trying to learn about AI and build something from it but didn't get a proper roadmap on what all to learn so I was hoping you could help me out with this channel 🙏 Keep going bro 🔥
Thank you Kshamith. Yes , I am going to create a playlist on GenAI tools and tech I hope it will help you out on your learning. I am using Excelidraw to create the notes.
Were you able to run it as a langchain retriever? When doing pip install the integrations folder is not getting installed and this is causing no module found error
Can you share the snapshot of the code and error
Hello Everyone please go through this link to find the Notebook used in the video. github.com/AIwithHimanshu/Colpali_practice.git
You should share the git code as well. Waiting for the Streamlit app video. Keep doing the good work
Thank you Jatin. Please find the notebook here github.com/AIwithHimanshu/Colpali_practice.git. I am working on that video. You will find it very soon.
Good stuff Himanshu
Thank you Sumit