Introduction to ollama

What Is ollama ?

Ollama is an open source tool which allow to access Large language models (LLMs) in the local system instead of using Large models over cloud.
Like openAI model chatGPT runs on cloud but with the help of ollama we can run models like ChatGPT locally.
Example:- 

• llma 3
• Mistral
• Gemma
• DeepSeek

These models can be run locally with the help of ollama.

Why Ollama is build?

To understand ollama firstly we have to understand what are the problem which have to face by AI models before using ollama.

How the AI models were used?

User -> Internet -> AI company server -> model processing -> response

Here the models instead of running in the local system AI models use any company servers.

Problem 1:- Privacy Issue

Suppose any company have some confidential data like- employee record, customers information, financial report, etc.  and if we use any cloud based AI the process which should be followed 

Company data -> Internet -> AI provider server

Now the data is no more confidential and out of the control of organization, that’s why company want local AI solutions.

Ollama solution:- ollama provided a locally running Large model which maintain the confidentiality of the data and process the query locally.

Company data -> local computer -> ollama -> local model

There is no chance of data leakage.

Problem 2:- API cost

Cloud AI is paid service.  For each request company have to pay some charges.
Higher the request = higher Cost $
API bills can be very high which can be problem for startup companies.

Ollama solution: ollama provides an advantage which is one time download.  When you download the model you can use it without any limit and this is also cost free.

Problem 3:- Internet Dependency 

Cloud AI only can be run when there is stable internet connection .
No internet = no API
Suppose the internet connection are off like in flight, remote village, company network is down then you cant access the models.

Ollama solution: since ollama provides one time download feature which means it do not need any internet to run the model which means it also save the internet cost and it is not dependent on internet.

Problem 4:- Developer Complexity 

It was difficult to run the local models  because to run the model developer have to install various dependencies like:

• Install python
• CUDA setup
• Install Dependencies
• Configure hugging face
• Understanding Quantization  

These all works have to perform by the developers which can also confuse the beginner developers.

Ollama solution: ollama provides a simple command 

Ollama run llama 3 

It automatically install all the dependencies which is required by a single command.

read more about ollama:
next topic :  is Ollama free? and ollama workflow → read...