> ## Documentation Index
> Fetch the complete documentation index at: https://notes.kodekloud.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Demo Customizing an Existing Model
> This tutorial teaches how to customize an Ollama model for use as an AI assistant in a financial institution.
In this tutorial, you’ll learn how to tailor an Ollama model using a `Modelfile` to serve as an AI assistant for a financial institution. We’ll walk through each step—from creating the file to running queries—so you can adapt these concepts for your own use case.
Make sure you have [Ollama][ollama-docs] installed and configured on your machine before you begin.
## Table of Contents
1. [Create and Open the Modelfile](#1-create-and-open-the-modelfile)
2. [Define Base Model & Parameters](#2-define-base-model--parameters)
3. [Add a System Prompt](#3-add-a-system-prompt)
4. [Build the Custom Model](#4-build-the-custom-model)
5. [Interact with Your Custom Model](#5-interact-with-your-custom-model)
6. [Example Financial Calculation](#6-example-financial-calculation)
7. [Links and References](#7-links-and-references)
***
## 1. Create and Open the Modelfile
Run the following commands to create an empty `Modelfile` and open it in your editor:
```bash theme={null}
touch Modelfile
code Modelfile
```
## 2. Define Base Model & Parameters
Specify the base model and adjust its creativity by setting the `temperature` parameter:
```text theme={null}
FROM llama3.2
PARAMETER temperature 0.3
```
| Directive | Purpose | Example |
| --------- | -------------------------------- | --------------------------- |
| FROM | Selects the base model | `FROM llama3.2` |
| PARAMETER | Configures model hyperparameters | `PARAMETER temperature 0.3` |
## 3. Add a System Prompt
Provide context so the model acts as a specialized AI assistant. In this example, we name it **Harris** and assign it to Growmore, a portfolio management firm dealing in INR:
```text theme={null}
SYSTEM You are Harris, an AI assistant for the employees of an investment and portfolio management firm called Growmore. Your job is to assist employees in managing client investments and portfolios. The currency you deal with is Indian Rupees (INR).
```
A clear, specific system prompt helps guide the model’s tone, scope, and domain knowledge. Always mention role, audience, and any domain-specific details.
Your final `Modelfile` should now look like:
```text theme={null}
FROM llama3.2
PARAMETER temperature 0.3
SYSTEM You are Harris, an AI assistant for the employees of an investment and portfolio management firm called Growmore. Your job is to assist employees in managing client investments and portfolios. The currency you deal with is Indian Rupees (INR).
```
## 4. Build the Custom Model
Use the Ollama CLI to build and name your custom model `harris`:
```bash theme={null}
ollama create harris -f Modelfile
```
Example output:
```bash theme={null}
gathering model components
using existing layer sha256:dde5aa...
creating new layer sha256:a3d6c7...
writing manifest
success
```
Verify your models:
```bash theme={null}
ollama ls
```
```bash theme={null}
NAME ID SIZE MODIFIED
harris:latest 267a012ab49f 2.0 GB 6 seconds ago
phi3:latest 4f2222927938 2.2 GB 2 hours ago
llama3.2:latest a80c4f17acd5 2.0 GB 25 hours ago
```
## 5. Interact with Your Custom Model
Start an interactive session and ask Harris some questions:
```bash theme={null}
ollama run harris
```
```text theme={null}
>>> what's your name?
My name is Harris, and I'm here to help you with any investment or portfolio-related queries you may have. How can I assist you today at Growmore?
>>> what does growmore do?
Growmore is an investment and portfolio management firm that helps individuals and institutions achieve their long-term financial goals through strategic investment planning and portfolio management.
We offer a range of services, including:
1. Investment Research
2. Portfolio Management
3. Asset Allocation
4. Risk Management
5. Tax Efficiency
Would you like me to elaborate on any of these services?
```
Notice how Harris automatically uses INR whenever monetary figures are mentioned.
## 6. Example Financial Calculation
Here’s a sample future-value calculation Harris can perform:
```text theme={null}
FV = Future Value
PV = Present Value = ₹5,000
r = Annual interest rate = 12% = 0.12
n = Number of years = 5
Formula:
FV = PV × (1 + r)^n
Calculation:
FV = ₹5,000 × (1 + 0.12)^5
FV = ₹5,000 × 1.7623
FV ≈ ₹8,811.71
```
Breakdown by year:
| Year | Calculation | Amount (₹) |
| ---- | --------------- | ---------- |
| 1 | 5,000 × 1.12 | 5,600.00 |
| 2 | 5,600 × 1.12 | 6,272.00 |
| 3 | 6,272 × 1.12 | 7,024.64 |
| 4 | 7,024.64 × 1.12 | 7,867.60 |
| 5 | 7,867.60 × 1.12 | 8,811.71 |
**Total after 5 years:** \~₹8,812
***
You’ve now customized an Ollama model using a `Modelfile` and tailored it for a finance-focused workflow. Share your model with teammates or deploy it to streamline client interactions.
## 7. Links and References
* [Ollama Documentation][ollama-docs]
* [Dockerfile Reference][docker-link]
* [Modelfile Guide][modelfile-guide]
[docker-link]: https://docs.docker.com/engine/reference/builder/
[ollama-docs]: https://ollama.com/docs/
[modelfile-guide]: https://ollama.com/docs/modelfile/