u have cleared all the concepts in very simple and easy way
@CodeWithAarohi25 күн бұрын
Glad to hear that
@Sunil-ez1hxАй бұрын
What an awesome way of explanation
@CodeWithAarohiАй бұрын
Glad you liked it
@itsmeuttu2 ай бұрын
Best tutor for AI and ML , Thanks alot mame
@CodeWithAarohi2 ай бұрын
Most welcome!
@SHIVAMKUMAR-l4f8r27 күн бұрын
Great Explanation. Please Bring More Concepts related to GenAI
@CodeWithAarohi25 күн бұрын
Yes, Sure.
@Umairkhan-j8p2 ай бұрын
Wao Amazing thanks mam from Pakistan
@CodeWithAarohi2 ай бұрын
Thank you!
@arnavthakur5409Ай бұрын
Very nicely explained ma'am
@CodeWithAarohiАй бұрын
Glad you liked it
@AkulSamartha2 ай бұрын
Super awesome video Asrohi. Can you make one RAG app to chat with any multiple websites please.
@CodeWithAarohi2 ай бұрын
You can provide the link of multiple websites in the urls list.
@AkulSamartha2 ай бұрын
@@CodeWithAarohi Sorry. My question was, can we add chat history into this.
@howGnt2 ай бұрын
looking forward to hearing seminar about Lora-pro from U
@CodeWithAarohi2 ай бұрын
Noted!
@omkarsatapathy82092 ай бұрын
Hello madam, Omkar, this side. I’m very glad to see your video regarding that RAG model. But for somehow, I realise that it is not hundred percent running locally, we need to use Google API token key. I have use the same with the open AI after few recurrent and after few token processing, it is asking some billing method or credit card details to further. Can we have such a model where we can deploy rag pipeline from scratch hundred percent locally? we can fetch an LLM model from hugging face and download it and storage in our local drive. Create a victor data on our own or just a pie tenor, which am all the text token. That will be much more beneficial for me if we are going for a a business purpose. It is much more beneficial to run it locally with a discreet GPU. Can you please help me guiding on the same building a rag model from scratch using a LLM from hugging face? It can be any LLM of my choice. I’ll be hopeful to see that tutorial and develop myself.. thank you so much for your content. Your content are very beautiful, and it’s very informative.. just teach like a teacher in a classroom, thank you so much again…..❤❤
@sanjaybhan15852 ай бұрын
How to interact with multiple pdfs, and how much load of data will be handled by llm as a free tier
@noorahmadharal2 ай бұрын
Thank you for this amazing series of vedios. I have a question that we ca using Chroma DB for saving the embeddings so how can we see these embeddings in chroma db and aslo we have not use any chroma db connection link.
@CodeWithAarohi2 ай бұрын
We have created a Chroma instance with Chroma.from_documents, which stores embeddings in a Chroma vector database. In our code, we haven’t specified a persist_directory, so the embeddings are stored in memory only. To persist the embeddings and be able to reconnect later. You can use this code: vectorstore = Chroma.from_documents( documents=docs, embedding=GoogleGenerativeAIEmbeddings(model="models/embedding-001"), persist_directory="path_to_persist_directory" ) # Save the embeddings to disk vectorstore.persist() To inspect the embeddings stored in Chroma DB, you can use the get_all_embeddings() method query_vector = GoogleGenerativeAIEmbeddings(model="models/embedding-001").embed("your query text") results = vectorstore.similarity_search(query_vector, k=5) for result in results: print(result)
@NehaKothari-iz3hy2 ай бұрын
Plz explain fine tuining the hugging face model on custom data specially text to image generation
@CodeWithAarohi2 ай бұрын
Sure, Soon!
@hendoitechnologies2 ай бұрын
full course video about "Claude 3.5 sonnet AI model, API finetune" full course please
@CodeWithAarohi2 ай бұрын
Noted!
@petlovers2103Ай бұрын
thanks for detailed explanation
@CodeWithAarohiАй бұрын
Welcome!
@Umairkhan-j8p2 ай бұрын
I have followed your video, but the chatbot is still giving answers outside the provided context, even after using your system prompt and making adjustments. For example, if I say "I'm sad, write a joke for me," it still writes a joke. This is the issue I'm encountering. Could you please provide a solution?
@sunnycloud292 ай бұрын
how to create the same on a CSV dataframe?
@CodeWithAarohi2 ай бұрын
Just load the data from csv file. Eg: from langchain_community.document_loaders.csv_loader import CSVLoader file_path = ("test.csv") loader = CSVLoader(file_path=file_path) data = loader.load() for record in data[:2]: print(record)
@FahadRamzan-ri4cr2 ай бұрын
I get this error while I run last cell of that basic rag --------------------------------------------------------------------------- AttributeError Traceback (most recent call last) Cell In[13], line 1 ----> 1 response = rag_chain.invoke({"input": "what is new in YOLOv9?"}) 2 print(response["answer"]) AttributeError: 'int' object has no attribute 'name'
@shobishobi170415 күн бұрын
I am not able to install chroma facing issue
@CodeWithAarohi14 күн бұрын
Please mention the issue you are facing.
@AbhishekSingh-od8syАй бұрын
is it paid maam ??
@CodeWithAarohiАй бұрын
NO
@clarkpaul3489Ай бұрын
mam can you please complete the generative ai playlist
@CodeWithAarohiАй бұрын
Yes, Sorry for the delay. Just busy with few ongoing projects.