Video

How about confidential data

Disliked, Jokic is the GOAT

Thanks. You know how use paligemma without higgingface? For example I download pali models on my pc and i need make inferences using my gpu with not internet connection

Hi, thanks for a great video, it worked well but how to save those embedding, like I am using a static data and it won't change

Why would I use this if I can just copy the link, insert it into ChatGpt and ask the same question?

Please make more RAG applications with advance techniques with larger context model

Very nice tutorial, I was actually looking into nim and found your video. I have a few questions I want to ask you, can I get your discord?

Could you please post your code used in this tutorial?

And what if my data is not in that format because I have a few law judgements and it's not possible to format the data in that way

Thanks for the video. But what models with what configuration could be trained with free tier gpu..? Maybe phi3 mini?

Great video! is it only for english?

HI. thank you for this video. I am using a server, and we are not allowed to use anything on baseline, but have tyo create docker container. I have installed llama in docker following the command docker run -d --gpus=all -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama and i am able to run llama3 from ollama with the command docker exec -it ollama ollama run llama3 Now, could you please tell me how can i follow your way to use ollama for embedding? i want to use llama3 from ollama as embedding model like you did in the video.

Create a video on how to fine-tune multi-modal LLM models using custom image datasets.

Hi Mosleh i try to get an appointement with you but your link don't work.

thank you

Good video. LBJ is far from GOAT though

Can you implement evaluation with qdrant, ragas or some-other fav framework, langchain, langfuse (open-source alternative to langsmith)

You could have used a pre-trained embedded model for feature extraction. I believe the results would be better than a text generation model such as llama 3 for feature extraction.

I couldnt see ur any day I can book, dont u have a discord or something?

Thank you. Also why use Mistral 3 vs nomic-embed

Can you do a tutorial on how to fine-tune Falcon 2? There isn't much content on it

simple but awesome explanation.

By specifying the model in the ollama.embeddings() call and in the OllamaEmbeddings class, what goes on behind the scenes and how is that model utilized in that scenario? Are there advantages to different models specified for the embedding process?

Hey Buddy, I've been noticing u from a while now on this channel Can u help me improve my RAG? I have everything ready and working just wanna optimise it

Hi Mosleh, thanks for this. I keep getting error when trying this with llama3. This worked perfectly with llama2? What could be the reason? I have both llama2 and llama3 installed. Actually I tried first with llama3 and then installed and tried with llama2. With llama3 I keep getting error that it cannot establish a connection, even though I could see that llama3 is running on port 11434

Can you make a video of this in vscode

what tools do you use to generate the mind map?

Thank you!

Gr8 Video, Super Userful :)

You ran LLama 3 8B locally on a Mac?!

Thank your for your explanation. I will upload your video to chat gpt so he can do the understanding part for me.

great video 🫡 could i expect an advanced tutorial on building an chatbot using gpt-4o api and implementing RAG

Hey! What are your computer specs? Wondering how that may affect speed, either positively or negatively.

How to solve it

Getting Error --------------------------------------------------------------------------- ReadTimeout

😊

Cool

Hi man! nice explanation. I was also trying to do that at my end. But I am getting some validation errors: raise validation_error pydantic.v1.error_wrappers.ValidationError: 2 validation errors for LLMChain llm instance of Runnable expected (type=type_error.arbitrary_type; expected_arbitrary_type=Runnable) llm Don't know why its happening. Can you please tell me how to resolve this

How is different from visual Bert ?

Is it true that the embedding values of the three methods are different for the same sentence?

Thanks for sharing :) In the initial package installation I had also to run: `pip install llama-index-embeddings-ollama` in order to run `from llama_index.embeddings.ollama import OllamaEmbedding`.

Em PTBR czcams.com/video/0VtGC_N3Rvk/video.htmlsi=s5QDIeDhtLmYlZxb

What about without using gpt 4?

Hello, what if i wanted to use the rag agent for a crm website how would that work

I, too, have embarked upon the arduous journey ofRAG, encountering a similar quandary wherein the retrieval mechanism, much to my chagrin, procures contextual information that bears little to no relevance to the query at hand. My hypothesis is that the embedding model, the very foundation upon which this edifice is built, is the root of this discrepancy. As my endeavors lie within the realm of the Indonesian language, I humbly beseech thee for any sagacious counsel or erudite suggestions that may illuminate the path towards a resolution

Amazing habibi

Hi! thanks for the great example. Have you tried to ask more questions e.g. "Which team has the most 3-point shots?"?

Nice

I was scared a little bit when your voice changed lol 2:18 But good video overall, thank you

Great ❤ Awesome lesson, Please look at fine-tuning this existing model with many documents for Ollama models. I looked everywhere and couldn't locate one without utilising an API or Langchain.