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About half way through, video is excellent, nicely explained, very clearly done with good pace. No music is such a treat!

Hello, thanks for the great tutorial. I'm stuck at this section: "db = sqlite3.connect("example.db") db.enable_load_extension(True) sqlite_vec.load(db) db.enable_load_extension(False)" I'm doing everything but it says "OperationalError: The specified module could not be found." on sqlite__vec.load() side. Can you help me on that?

Awesome video <3 Thank bro <3

Awesome content. Request you to categorise your channel videos into ordered playlists

Full-text tutorial (requires MLExpert Pro): www.mlexpert.io/bootcamp/langgraph-basics

Can I export the chatbot so I can integrate it into an app?

can you share the notebook?

Hello Venelin, thanks for the video. Iface this problem when running the query: "I encountered an error while trying to use the tool. This was the error: StructuredTool._run() missing 1 required keyword-only argument: 'config'. Tool list_tables accepts these inputs: list_tables() - List the available tables in the database" any help here? Thanks

I’m trying to fine-tune the LLaMA 3.1 8B model without quantization, but when I try to use the pipeline with the unquantized model, I encounter this error: Trying to set a tensor of shape torch.Size([128256, 4096]) in 'weight' (which has shape torch.Size([128264, 4096])), this looks incorrect. Do you know why this is happening? maybe i'm using the wrong pad token idk. Thanks in advance

Amazing video

Full-text tutorial (requires MLExpert Pro): www.mlexpert.io/bootcamp/rag-from-scratch

Hi, how's it going? I want to integrate a chatbot into my website. NO WhatsApp. Is it possible to create a CMS to manage this chatbot?

Great tutorial as usual😊. I have two queries: 1. You are using sqlite-vec for fast retrieval? Otherwise just store query and response in any db and using cosine similarity on the customer query fetch the top most relevant response. 2. Why are you using LLMs here, is it just bcoz to get the concise and short answer? Because LLMs might hallucinate in some cases which i think can be more harmful sometimes.

if we want retrieve the images related to the text or the question will it be possible if yes how

Hi.. how can i subscribe to ml expert

If we apply the same approach to a dataset with another language like France or Arabic, will the approach change? Assume same columns structure, and names like you showed in the video.

thankyou so much for the vids.... Amazing content... just one query Shouldnt top be max(ys)?? at 24:27??

That's one more insightful tutorial. Thank you Venelin!

If you find a function that can completely parse any given python function into a valid tools entry, tell me :)

Can llm be used for controlling robots ?

Keep the good work

Great videos

Hi

Full-text tutorial (requires MLExpert Pro): www.mlexpert.io/bootcamp/llm-function-calling

So i guess this is another tutorial that ends after writing the basic thing with a "in the next video we'll make it do something" but that video never came.. I just want a single full start to end tutorial of a neural network....

can we follow the same steps to finetuning another model LMM like Mistral AI ?

is there any method to correct that mistake about calculating profits?

Nice. What I am looking for though is a similar system for not just one document but one that is suitable to shat with a corpus of 1000s of documents in my archive, and - to be greedy - to create a relational map from the perspective of the query. Any hints?

Is it safe to use huggingfaceembeddings for confidential data? How secure it is?

anyoneelse have the issue with loading dataset????

ruclips.net/video/3crJNnAXd6w/видео.html

How do you modify the code so that it starts with the same document you already ingested when you restart the app?

Hi Thank you for sharing your knowledge. Please share the code of this video if possible. Thank you.

Full-text tutorial (requires MLExpert Pro): www.mlexpert.io/bootcamp/ragbase-local-rag

Thank you in have watch several videos on llama fine tuning With lots of differences you are the best ! Especially anout dataset and how you formatted it

I'm making my final year project and it involves training a model on custom data, thanks for this video.

Дали base model-a ще може да се тренира с двойки въпрос-отговор на Български?

when i run trainer.fit(model,data_module) 54 has_train_dataloader = is_overridden('train_dataloader', model) 55 if not has_train_dataloader: ---> 56 raise MisconfigurationException( 57 'No `train_dataloader()` method defined. Lightning `Trainer` expects as minimum a' 58 ' `training_step()`, `train_dataloader()` and `configure_optimizers()` to be defined.' MisconfigurationException: No `train_dataloader()` method defined. Lightning `Trainer` expects as minimum a `training_step()`, `train_dataloader()` and `configure_optimizers()` to be defined how to fix

Sir could you share the text summarisation with N-grams using deep learning back end code 😢

I trained it with 2 epochs and the result was amazing! Nice explanation btw!!

that's great; llama-parse is sweet. Please make a video showing how to use a knowledge graph index in conjunction with the vector DB!

If you don't know what are you doing then don't make videos !! 🤬

Great breakdown. Keep it up

nice wutang shirt and great content. thanks

Can we fine tune to 2bit model ?

Great video! Could you share how to build the webpage with FastAPI like you did? or any tutorials, thanks!

Im looking for this ❣️

Great stuff as usual. Very useful info!

Full-text tutorial (requires MLExpert Pro): www.mlexpert.io/bootcamp/fine-tuning-llama-3-llm-for-rag What performance did you get with your fine-tuned model?