Install and Run OLLAMA on Linux Machine

So many tech guys already share how to install the OLLAM. I wont say too details. Just a brief step for you.

  1. Prepare a Machine with good GPU, CPU and > 16G RAM. (Raspberry Pi can run with the Deepseek 1.5B, other………. Please chec my last post)
  2. Install update your linux repos.
    sudo apt-get update -y
    sudo apt-get upgrade -y
  3. Install Ollam by the follow command
    curl -fsSL https://ollama.com/install.sh | sh
  4. Run the LLM model, if you wont have the model at your machine, it will be download automatically.
    ollama run <model>
    e.g.: ollama run deepseek-r1:8b
  5. The model will be downloaded to /usr/share/ollama/.ollama/models/
  6. what model you can run? Check here
    https://ollama.com/search
  7. OLLAMA command line is a little bit similar with Docker, check this.

PS: You also can install OLLAMA at WINDOWS, please also check OLLAMA website.

Lets try your own AI locally!

#OLLAMA #Model #AI #CPU #GPU #CUDB #RAM #RaspberryPI #Docker

Raspberry Pi 4b 4G Ram with Deepseek 8b….

Answer is ……. Fail………..

I cannot run Deepseek 8b on my Raspbeery Pi 4b 4G Ram version…….

OLLAMA keeps loading and crash and load again….. Suspect the storage full…..

Anyone?

2025-02-06

Hooray!!! Model directory MAP to share drive.

ERROR!!!!!!!! Not enough Memory!!!!!!!!!!

#AI #deepseek #raspbeerypi #R1-8B #memory #ram #ERROR

Enhance Internet performance by using the right Public DNS servers

If you are thinking of how to enhance your Internet performance, it is great that you can subscribe a higher bandwidth Internet service. But is it the right way?

No really.

Increasing the bandwidth cannot shortern the latency between you and the destination server. But You cannot control our provider’s network path.

Under the current Web server depolyment, using the Content Delivery Network to deliver the content to Internet is a comment way. However, your network provider’s DNS server may not response the optimial server for the request domain. Therefore, you cannot enjoy the lowest latency between you and the request server.

HOW to?

A little measurement you can do, you can try to make a query to several publilc DNS servers, the reponse result may not be the same. For Example, by 8.8.8.8 Google or 1.1.1.1 Cloudflare. Based on the result, a simple ping test you can perform and record the lower latency one. Finally, you can setup a bind server to forware the domain to that DNS server to have a better Internet performance.

Reference what our work. Feel Free to discuss.

https://www.bgptrace.com/DNS/running_result.html

#DNS #Internet #Measurement #Ping #Latency #CloudFlare #Google #1.1.1.1 #8.8.8.8

Global Latency Map – by using RIPE Atlas

Using RIPE Atlas to perform the global network latency map. Atlas Probes are existing world wide and let you to perform the measurement by using your CREDIT. Self developed Python automation program used to perform the test by RIPE Atlas API.

Access the following to see our work.

https://www.bgptrace.com/atlas/ping_map.html

Can Starlink to be a testable probe?

More Information: https://atlas.ripe.net/

#ripe #Internet #measurement #python #automation #latency #starlink #atlas

Deepseek 1.5b vs 8b version

Well, we all expect that 1.5b and 8b may have a different of AI’s knowledge.

We made a test,
1. 1.5b we are on Raspberry PI 4B 4G Ram.,
2. 8b on virtual machine with AMD Radeon and 16G Ram on Ubuntu.

We only ask a question.

“what is the difference between you and chatGPT”

  • 1. 1.5b versions

  • 2. 8b versions

The knowledge base of course 8b will be better. However, we will most concern of the resource usage. Can Raspberry PI CPU base can process this efficient?

#deepseek #AI #CPU #raspberrypi #GPU #nvidia #CUDB #AMD

Deepseek on Raspberry PI?????

Tech guys are interested in how AI and LLM model processing on an IOT, low power devices such as Raspberry PI.

But??!!!!

NO GPU!!!!!!!!!!!!

How to run the AI model????

OK, We dont want to talk about how to install and run on OLLAMA.

We have tried on 1.5b version of Deepseek on our PI4 4G RAM device.

Amazing that it works! However, you cannot expect the response time and token would be good enough for fast response.

By this kind of success, we can imagine that more other model can be running on CPU based IOT device. Therefore, will the home assistant widely adopt?

Let see……………….