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I think it looks good, but I wasn't watching the stream.

In chat completion is there something like chat request with a pdf file?

Matt, your subtitles are greeting in the way of UA-cam subtitles

Hey Matt. What's your thoughts on the snake eating it's tail thing going on with LLM models and training now?

I thought I was doing well until you went from cd dify to cd docker, then you completely lost me as my cmd line doesn't recognise the eza -ahl, any thoughts? Thanks

Thank you for these videos. They're really awesome. The format's great - it's casual, informative, relaxing. Also, hello from Europe!

Oh god, there is nothing more annoying that forced color jumping ticktock bullshit subtitles! Unsubscribe!

Nice show!

There is only one viable ocr program and it sucks! I can only get OCR to work by using Ai.

Can you explain why the Windows Executable is significantly slower than when running in WSL? I also found that when running Ollama on Docker with WSL2 backend is faster than just running in WSL. Why!?

Hey Matt don't you have the feeling to be Professor Gerald Lambeau asking Will Hunting to do simple maths ? I know I do :) This question is for boths Matts (@technovangelist and @matthew_berman)

Great job Matt, I enjoyed the live stream.

👌

As usual, wonderful video, Matt. This is exactly the kind of question that I make to myself when learning ollama. And here’s the answer on a silver tray.

Keep up the great myth busting.

So I made a Discord bot that streams from the Ollama API to Discord. Discord has an API rate limit of like 3 requests per second, so I had to buffer all the stream payloads in memory and dump them in chunks to Discord. I did this in NodeRed if anyone wants the code. I had to implement the HTTP client again from the TCP layer to support streaming, but have wrapped it up nicely into a single function node. I should also mention that it supports multiple conversations concurrently (without mixing up the streams).

Can I train model via chatting with the model? how to do it

Not sure if my original comment posted or not. Either way, Mervin Praison has a neat little add-on for PraisonAI which makes the training process a bit less painful.

Great educational content. Bravo! 🎉🎉🎉

Nice spin on things.

When accessing Ollama via the API, can we set keep alive to forever? If yes would it prevent the API from later switching models?

Can ollama run on Gpu instead of Cpu? Also how do you incoporate ollama chat you build into website? Thanks for sharing good content🎉

Ah - that discord... says invite expired ! ?

Good day, Matt, hopefully, this is my last question about the Private GPT installation. My laptop has arrived. I have installed an M.2 2T primary drive and a secondary 2T SSD. Q: After installing Ollama, Docker, and WebUI, can the models be stored (directed) to the secondary SSD to preserve space on the primary M.2 system SSD? If so, when do I pick where to store the models during their installation?

Local!

hello, any idea how to set keep_alive when running the windows exe ?

I have a noob question. If anybody can upload a model on Ollama, is it possible for a malicious user to upload malware disguised as a model? And are there measures to prevent such a scenario.

Can I generate an installable app to deploy it in own infra? Which code language use it behind? Can I have access to code generated to custom behaviour?

Hey Matt, I was really excited for this video, then only to realize theres no mention of Ollama in it!?!? I have a project on the go where I'm trying to build a multi container app using docker-compose where the containers are backend- fastAPI, frontend- Nextjs and llmServer- Ollama. I'm running into problems having the backend connect to the Ollama server ... I get the dreaded [Errno 111] Connection refused

Any tutorial on model creating from custom data,like pdf s? Like for companies?

Please share the link of the video for reducing the model size for specific tasks, example, only weather, is wouldn't need the hole context for this

1973

Man. I love it. I already subscribe to it. Something I really will be crazy to know is how to story my ollama local models in an external hard drive in Mac. As you know macs doesn't have much space. So, i bought a special hard drive that runs at 40G/sec to have models and other stuff and I will love to have the models in there than in my internal hard drive. Thanks for the great content and explanations.

Matt, I do not see COBOL (of any flavor) especially for PCs; e.g., MicroCOBOL and or GnuCOBOL 😢😢😢 Which Ai Code Assistant can GnuCOBOL? Is LaTeX not considered a programming language? Or is LaTeX considered native to all Ai entities?

Wonderful video, Matt. Thanks so much for sharing this.

I love your videos! Your explanations are amazing, thank you!

Thank you!

🙏🙏🙏Please how to add vision model MiniCPM-V 2.6 to ollama? openbmb/MiniCPM-V-2_6-gguf

I'm really enjoying this series. Thanks.

what location to run that download hugging face model command? and where does it download to? same location as the others wheres that?

any1 wana swap code for tokens?

I am very interested in FABRIC, and I will probably get into a serious use of it. I think it would be very useful if you create a video taking one or two of the patterns that may not be configured to your exact use case and demonstrate how you would modify them for your use case. This type of use case from an experienced Generative AI Aficionado can be very helpful for more novice users. Thanks for all your videos. I watched a lot of them and I will watch a lot more.

is there a way i can fetch the whole response in a single response object

"If, for example, I have more than one model downloaded, and one is chat, another is multimodal, and another generates images, can I make it so that Ollama chooses which model to use based on a prompt, or does it by default use the one you've chosen with the `ollama run` command?"

Hey Matt! Off topic comment but I guess I'm feeding the ol' UA-cam algorithm anyway! I haven't watched your entire backlog so apologies if you've already covered this, but I'd love to see some content / videos on the following topics: 1. How can you use ollama in a production environment. Topics around infrastructure, reasonable techniques (e.g. handing off processing to async jobs when possible), cost, etc. I'm not sure how common this use case is but I am evaluating using something like llama 3.1 to help summarize some potentially very large text files and weighing cost differences between using something turnkey like openai's APIs vs figuring out hosting myself (well my company. There seems to be a lot less on production hardening some of these open source models (or I just haven't been paying attention!) 2. A "state of the union" high level overview of the options available to software developer new to using AI. This you have covered in a lot more detail in various forms, but an overview of what tools are actually at a persons disposal in terms of trying to use AI to solve some problem. When I first started looking at this stuff I thought the only options I had were buying a bunch of super computers to train models and learning a lot about doing matrix multiplication. But we have RAG, we have "fine tuning", we have modifying system prompts... a sort of high level overview of what a layperson can do, and perhaps where reasonable off-ramps for more advance use cases are would be super helpful (i.e. when do I need to brunch up on my linear algebra? :)) Thanks for your work!

Outstanding video. As a complete newbie this was intriguing, well explained and engaging. New subber and bell set

Excellent content Matt! Congrats! Keep on going.