I Analyzed My Finance With Local LLMs
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GitHub repo 👉 github.com/thu-vu92/local-llm...
🔑 TIMESTAMPS
================================
0:00 - Project intro
1:35 - Sponsor (Coursera)
2:04 - Why using local LLMs?
3:34 - Install Ollama
4:14 - Run local Mistral model
6:17 - Run local Llama2 model
7:27 - Customize LLMs with Ollama
9:53 - Access Llama2 with Langchain (Python)
10:45 - Categorise bank transactions
14:46 - Create personal finance dashboard
17:24 - Conclusions
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Пікірлер: 344
This is such a great video. Thank you for making it. I had no idea this sort of thing was possible and I'm finding all sorts of ways to take advantage of it now.
What an amazing video! This is definitely a personal project that I've wanted to tackle and while I'm familiar with other languages, I'll definitely use your video as a guideline.
This is great. We're in the process of integrating LLMs into our "what if" scenario modelling platform and this gave me a few ideas on next steps. Sharing this video with my dev team!
Wow absolutely wow, thank you for such a great project, so many ideas ringing in my head. Cheers
Hi Thu! Last year I had referenced your panel dashboard video to build my personal finance dashboard. I like seeing how you built yours. Your content is very useful. Thank you!
This was an excellent video - many thanks for sharing!
Always good to see more people bringing data skills to understand personal finance.
Thank you so much for making this video. Subscribed, this is exactly the content I look for
Excellent video, I used the concepts to enhance a project that I had already started in R and it worked fine, but so slow in my computer (like 5 min to analyse 10 registers). Now I know the concepts and I`ll keep experimenting with other LLM models. Thank you!
Love the video! The beginning sets up the project perjectly and the tutorial is very easy to follow!
Wow this is fantastic video. Thank you, Thu!
thank you! this is a project i'd love to try, keep up the good work 😊
Thank you for sharing this dear! You covered the basics and shown the path to a great first goal with your own custom on premise and well licensed LLM. Huge!
@Thuvu5
2 ай бұрын
You are so welcome! Glad it was helpful 🙌
Really awesome explanation! I am going to use this. Thank you Thu!!
Amazing work you put in here. This is inspiring
Thanks for the great overview of using aa local LLM Thuy! Very useful and informative.
J'ai adoré, vidéo super clair allant droit au but et qui nous la joie d'aller découvrir le code
Thanks so much! It giving me inspiration for using this in a security analysis context.
Thanks for the demo and info. So detailed and analytics are great. Have a great day
Incredible intro video for the semi technical about how chat gpt and similar models will be used in daily life to improve the mundane tasks, with a side of cautions about incorrect answers and computational limitations! Great balance, I’m already sharing it around our team 😊
@Thuvu5
3 ай бұрын
Thanks a lot for your comment and for sharing it around! Really appreciate it 🤩🙌
Thanks for the video. Nicely done and presented, educational with an interesting use case
Thank you so much. 🥰It is so well explained and a very cool project. I think LLMs are a powerful tool and running them locally will make it safe to share critical information with them.
@Thuvu5
3 ай бұрын
Thank you, really appreciate it! ❤
this is great.. thank you for the breakdown of all these options
Fantastic! Your videos are always good surprises at my feed.
I learned so so much watching this. Thank you so much.
Great video to start using LLM! Thank you for sharing!
I was looking for THIS! Thanks!!
Well done I'll try and re-create this. Thank you once again
this is one of the best videos I watched about llms
Thank you so much for sharing this with us!! I’ve been looking to do this for years but just thinking about the task ahead, I would give up. I will definitely analyze my own financial statements. Thanks mucho gusto!!
Are you a real human? I have NEVER seen an author on youtube cover so much incredible knowledge in such a short video. This is absolutely AMAZING!!! Thank you
@martingrillo6956
27 күн бұрын
Her being an AGI would make perfectly sense
Amazing. Thank you for sharing this, I learned so much!
This is great! I was recently experimenting on a personal finance tracker dashboard and connect it to a chatting apps, so the user could easily input their financial activity by only typing it. On the process, i try to use chat gpt to simplify and generalise the format so we can input the data faster, never have i thought that it could be done by a local LLM. Looking forward for your next video.
Great video .. The one project which I wanted to take up during my holidays .. Learn in the same time have a view on my personal finance ..
You are awesome! Thanks for making this video.
Amazing job explaining this!
You are a very good presenter, easy to follow. Nice content
Awesome research as always!
Love it , i am subscribing instantly , i have a lot of questions.
Very concise and informative video. I appreciate it.
Thanks for sharing with us, much appreciation! ❤️
@Thuvu5
3 ай бұрын
Thank you for watching! ❤️
ayo, i'm just doing my first step that's logging every expenses i got since the start of this year i'm just thinking about doing some sort of software that help me manage my expenses and savings and this is exactly what i think of thank you for the high quality video
incredible, loved the content.
I see how this is useful for being one's own accountant :) Super!
Outstanding video, especially for this beginner. Didn’t know you could run the models locally. Those ollama layers look like docker, fascinating how the context is setup. Time for me to spend some cycles on all your vids, not just the couple I’ve casually looked at. Thanks!
@Thuvu5
3 ай бұрын
Glad to hear you found the videos helpful! Thanks for stopping by 🙌🏽
@pw4827
3 ай бұрын
Me too. I thought you need to have some monstrous supercomputer and spend weeks on configuring everything to run one of these models locally
Great vid, great content, and easy to understand.
Thanks for the great intro into how to get started with local LLMs. I'll give it a go after Tết 😄
@Thuvu5
3 ай бұрын
Happy Tet holiday! 😀🎉
Great insights and well explained!
Thankyou so much for this video. I relly like the explanation. Thanks
I love this video, thank you very much!!
Very well explained. Looking forward to you posting the github repo.
@Thuvu5
3 ай бұрын
Thank you for watching! I've added the repo link in the description 🙌🏽
Your videos are well thought out .. Keep them coming - Dont want you "retiring soon" 🙂
@Thuvu5
3 ай бұрын
Haha thank you for this! Don’t worry, with KZread I don’t want to retire anytime soon 😉🤗
Thanks Thu, just heard about local LLMs from my boss today and look whose video is on the top to help me out! 😃
@Thuvu5
3 ай бұрын
Hey Shivam! Thanks for watching! So happy to see your comment 😍🤗
I never ever ever comment on anything, but goddamn - what a great video/tutorial. Just finished playing with the notebook and I learned a ton!
@Thuvu5
2 ай бұрын
That’s so awesome to hear! Thank you so much for commenting ❤️🤗
Finally the text classification video that I was searching for
Great video... My 2 cents: we can force LLMs to respond only in json format by stating it in system prompt, so you get consistent parsable response always (I've tried with gpt4), also you can provide list of possible expense categories to avoid grouping them together later (like 'Food & Beverage' and 'Food/Beverage')
@martinmoder5900
2 ай бұрын
Yeah, it is very powerful! However, is llama2 also providing this?
@NicolasCerveaux
2 ай бұрын
@@martinmoder5900 llama2 and even gemma:2b does that too, but when I tried it still generated "new" categories, and the json answers would be "odd" like sometime it would modify the name of the expense.
Your content always useful! I like the Panel lots.
@Thuvu5
3 ай бұрын
Thank you so much! So happy to hear 🤩
@gmostafaali
3 ай бұрын
@@Thuvu5 💛
I loved this and hope to try this out for myself (though my programming skills are very rusty)
very good! thank you for sharing!
Thanks Thu, great demo of Ollama, sorry your arent going to be retiring anytime soon😢 I really like the multimodal model support in Ollama, llava is a great model to try and runs on not much RAM.
@Thuvu5
3 ай бұрын
Thank you Oliver! I would absolutely not mind making videos until I retire though 🤣. The multimodal support is interesting, I haven't tried it out yet but will look into those models a bit more 🙌🏽.
Nice. Might give this a try over the weekend. Just need to figure out how to get my banks data.
This is incredible, a bit far fetched from my skills and time in hands. But surely inspiring!
Thank you SOOOOOOO much for this !! this is an awesome tutorial
@Thuvu5
3 күн бұрын
You are so welcome! Glad you like it!
OMG this is inspiring I always wanted a 3rd party view about my expenses without loosing control of my data and this video hits the nail on the head.
@Thuvu5
11 күн бұрын
So glad to hear! Good luck with your project 🤗
This is a great video.!I learned a lot Thank you so much! 👍🎁🎁
Great info, and thanks a lot
Thanks, That was inspiring indeed :)
Amazing and inspiring 😊
If you want to give data as many as the number of tokens of the model. You don't need to calculate and know by hand. Instead, you can do this with "chunks" in Langchain. nice explanation thank you
Great video like always Thu! You never fail to fascinate me with your content as you make Data Science seem so fun to experiment with! Do you happen to have experience with the Bloomberg Terminal or any project idea to do using it? Would be amazing to know what you think of it! 🥰💛
@Thuvu5
2 ай бұрын
Thank you for such kind words! No I haven’t had the chance to try out Bloomberg Terminal. It’s perhaps worth looking into for a future video 🤔
@palakgoel5656
2 ай бұрын
@@Thuvu5 excited and hoping to have a look at it 💫💕
Love this!
Well explained ❤
thats a awsome vid thanks 🥰
🎯 Key Takeaways for quick navigation: 00:00 💲 *Reviewing Income and Expense Breakdown* - Explained the process of analyzing financial transactions. - Talked about classification of expenses into categories. - Spoke about using low-tech ways and an AI assistant for classification. 02:16 💻 *Running a Large Language Model Locally* - Discussed different ways to run an open-source language model locally. - Listed various popular frameworks to run models on personal devices. - Explained why these frameworks are needed, emphasizing the size of the model and memory efficiency. 04:18 📚 *Installing and Understanding Language Models * - Demonstrated how to install a language model through the terminal. - Showed the interaction with the language model through queries in the terminal. - Assessed the model's math capabilities, showing a failed example. 06:48 🎯 *Evaluating Expense Classification of Language Models* - Checked if the language models can categorize expenses properly through the terminal. - Demonstrated how to switch models, correctly installing another model. - Showed the differences between the models and preferred one due to answer formatting. 08:24 🛠️ *Creating Custom Language Models* - Explained how to specify base models and set parameters for language models. - Demonstrated how to create a custom model through the terminal. - Discussed viewing the list of models available and building a custom blueprint to meet specific requirements. 11:46 🔄 *Creating For Loop to Classify Expenses * - Discussed forming a for loop to classify multiple expenses. - Detailed how to chunk long lists of transactions to avoid token limit in the language model. - Mentioned the unpredictability of language models and potential need for multiple queries. 14:32 🔍 *Analyzing and Categorizing Expenses* - Demonstrated how to analyze and categorize transactions. - Showed how to group transactions together, clean up the dataframe, and merge it with the main transaction dataframe. 15:14 📊 *Creating Personal Finance Dashboard * - Detailed the creation of a personal finance dashboard, that includes income and expenses breakdown for two years. - Introduced useful visualization tools such as Plotly Express and Panel, giving a short tutorial on how to use them. - Demonstrated the assembling of a data dashboard from charts and supplementing it with custom text. 17:02 📈 *Visualizing Financial Behavior Over Time* - Demonstrated the use of the finance dashboard, drawing observations. - Concluded with a note on importance of incorporating assets into financial management. - Highlighted the value of running large language models on personal devices for tasks like these. Made with HARPA AI
Excellent video and practical application, you didn't get to cover pydantic much which solves a current challenge with LLMs. As for the dashboard, maybe another framework or approach with less or no code could be be more efficient :)
I've noticed that most LLM understand that you would like a CSV formatted output and you use that to get more consistent output.
pretty cool work
Cool project! I'd like to try it myself. One interesting idea is to have the LLM generate a memo field for each transaction (which can be controlled via prompting). Then by embedding these and doing hybrid retrieval, you can search in natural language as well as by metadata for transactions.
@Thuvu5
3 ай бұрын
That’s an interesting idea! Would love to see how well the retrieval works 🤗
That's awesome. I would also use Llama to write the code for generating plotly charts/dashboards haha!
As always, high-quality content from a highly competent woman!
@Thuvu5
3 ай бұрын
That's so kind of you, I'm trying to be ;)
I was wondering where I listened to this music. Amazon learning has this background music. Thanks for sharing :)
Thank you! 🦙
As a Javascript coder, this was a mindblowing video, I had no idea Python was this powerful.
Fantastic video
This is a great inroduction to Ollama
love your videos
Thanks again for another wonderful video. Ollama is now available on Windows as a preview. I used that preview version on the solution you shared here and it worked great! 🙂 Can you recommend a tutorial on the panel library? Thanks in advance.
Thanks for this video
I just read about the latest Meta LLAMA model that is supposed to be better than GPT4 for s/w dev! I hope that we can run it as a LOCAL LLM ! Thank You for this timely vid. ...
@Thuvu5
3 ай бұрын
Ooh that’s pretty cool! 🤩 So great to hear many models are approaching GPT4 capabilities 🤯
Great video. Very inspiring. Also...I used to live in Amstelveen (20+ years ago!). Funny to see that name in there.
@Thuvu5
2 ай бұрын
Oh haha, the world is small! 😀
Amazing!!
Great Work.
Great stuff 👏🏻
@Thuvu5
3 ай бұрын
Thanks for the visit! ;)
Nice showcase of that it's ok if things don't work out first try - there's another model / another try :)
Awesome video, learned a lot of new tools and want to try this out. For the dashboard, wonder if using Excel would be easier? Not sure.
Wow 🎉🎉🎉thanks 🎉🎉🎉
Thanks for the video! It was very clear and helpful. I'm curious, why didn't you use the Langchain CSV agent? Have you tried it before? If so, did you find it to be overkill or not helpful for this case? I'm new to Langchain and LLMs, so this video was incredibly informative. Thanks again!
Thank you!
Great Video! Still happy with Panel? Tried Gradio?
I am amazed