Відео

This was great, would love to see more content from you. Cheers!

Thanks for sharing the code.

You are a great teacher you clearly break concepts down and make it easier to digest the information. Thank you!

Very simple and knowledgeable video, thanks man -> Good work.

shouldn't there be a free way to access a local port on the internet other than ngrok?

easiest way around 2:12 is to paste the .txt into a markdown editor and save as .md idk why but it solves the line breaks.

Thx, very helpful.

Thanks, I hadn't heard of ngrok before today. This worked perfectly!

Great video. Is there somewhere to download the code you used? Currently, I am stopping the presentation and typing from your screen but there must be a better way. Thanks this is the best RAG description I have found.

What software are you using for the terminal and accessing ollama? I've managed to install ollama + an llm but I find the standard shell view a bit confusing. Thank you for the video!

Wow! Great video! You explained everything very clearly. I would love to be able to see how to do this using Langchain, etc... Thank you!

How can we train the model with our custom data so that it produces result based on given data

how to structure the response like json content

Top notch video ... Thanks a lot ... I would love to know if we can use GPT locally as a way of having other options for ollama.

As a newbie to this, you kinda jumped 10 steps here 3:05. Also, I'm on Windows and have no experience using linux. Any documentation on how to do this in windows?

Great tutorial David, clear and easy to follow. You just got a new subscriber 🦾

thank you for this amazing video

is there a way which can be used if I want to let Lama answer from its own knowledge base when my own data is not relevant or is not accurate to be an answer to the user's prompt?

Important nit to pick. These llama models are not open source in any sense. They are proprietary models but you free to use it.

Thanks for you series of videos. They are to the point and very comprehensive. Thanks again!

Я установил ngrok туда же в docker, и мне не приходится мириться с запущенным окном ngrok

how do I make ngrok run in the background in docker so i can close my terminal. I am new to docker and don't know how to do it. any help is appreciated.

Great video!! Please Make instructions how to run models which are MllamaForConditionalGen arch.

really appreciated. well made video, now i understood the crux of LangChain.

Really wanna appreciate this video. There are so many langchain videos but nothing clarifies the basics this well. Also given langchain gets updated very frequently to be clear with the core this is a beautiful video. Please make a series out of these. Cover all the basics needed , new approaches etc.

This is the true tutorial explain very well only important information that need to use to implement RAG. Thanks.

FileNotFoundError: spm tokenizer.model not found.

wow, excellent vid. Thanks!

I'm not a software engineer, and I have over three decades of experience not being a software engineer. I know how to program though. I've done it for like a while. Also I've been teaching programming, so there's that. In other words.

6:04 - talks about quantization (how you can, using a docker command quantize your GGUF file to a smaller size/bit format... well, I think they added that feature on huggingface recently. When I went to the model mentioned in the video, well, TheBloke's version of it, there's a button that displays next the the [Train] button, it's a [Use this model] button, when you click on it, you now have a choice "Ollama"... pretty nice! Thanks for this video it was extremely helpful.

7:52 ключ был виден

Is there a way to make same interface as in the video now (Documents, Prompts, Models as separate sections on the left menu) or there's no way and we are stuck with current lame webui version?

Thanks for the video, you kind of skip over the modelfile for the huggingface converted file at the end , how do you determine the prompt template to use ?

I liked how you used cosign similarity to show the actual chunks of matched text. Since this usually happens behind the curtains it was nice to have that extra insight. I like your style and just subscribed.

hi! What to do when i installed ollama with the sh script In linux? after cloned the repo...

Wow, thank you for this! :D

thanks1 I'm getting up to speed on all this info. I was wondering where to find these LLM models that Ollama Run didn't know about.

Amazing explanation. Thanks

i am just a beginer in all things AI and voila I implemented this video successfully' So proud that and my AI is running in my phone. Feel so empowered now. Thanks for a great video.

This helped me a lot. Great quality and good way of explaining everything. Thank you so much

where do i put the first code, im very beginner

Dude just made my doubts clear before I finished my tea.

for the life of me i cant figure out how to connect open webui to ollama. 127.0.0.1:11434/ show ollama is running. I tried: host.docker.internal:11434, 127.0.0.1:11434/ at open webui ollama api still unsuccessful. Went inside the docker (docker exec -it name) and curl 127.0.0.1:11434, still no good. I delete ollama, remove all docker image etc, still no good :( the regular container without port mapping works fine though. Great videos btw, i have watched all your videos and follow your tutorial, I hope you do more ollama and langchain videos.

I'm really impressed with the 27B version of Gemma2. It's working well for me as a usefully competent Russian language conversation partner/tutor, which is pretty amazing for something small enough to run locally. Mistral (7B) and Llama3 (8B) weren't quite sharp enough.

First of all Thank you for making this vedio!!, can you also make vedio on how to handle when mulitple text files are there. Thank you.

I really like the way you present this stuff so clearly and directly - you have a great teaching style. I'm going to keep tinkering with the chat app: it's fun! Glad I found this channel - thanks :)

Awesome structure and explanation !

This is a great video. You teach like a Professor. You're an expert and well talented! Your organization will indeed love working with you.

You're great!

Thank You!!