Install Ollama
Download and install the Ollama runtime for your operating system from the official Ollama website. Follow the platform-specific installer. Once installed, open a terminal or command prompt.
Coding / Intermediate
Build a local coding assistant with Qwen2.5 Coder · 7B
Set up the Qwen2.5 Coder 7B instruct model with Ollama, connect through the interactive chat interface, and complete a small reviewable coding task such as generating a quick sort function.
EstimatedSource checked 9/24/2026
LOCALRENTED GPU
Before you begin
- Difficulty
- Intermediate
- Software
- Ollama, Windows, macOS, or Linux operating system, Terminal or command prompt, Python 3.8+ (for optional Hugging Face Transformers path)
- Hardware
- For the publisher's 4.7 GB Ollama text package at a short 4K context, we estimate at least 10 GB GPU memory or 16 GB Apple unified memory. For a more comfortable starting point, use 16 GB GPU memory or 24 GB unified memory. These are capacity estimates, not speed tests; longer context and other apps need additional headroom.
CODING / OLLAMASOURCE-LINKED SETUP
Build a local coding assistant with Qwen2.5 Coder · 7B, step by step.
Set up the Qwen2.5 Coder 7B instruct model with Ollama, connect through the interactive chat interface, and complete a small reviewable coding task such as generating a quick sort function.
Choose a package Run its commands Check the result
01
BEFORE YOU BEGIN
The documented package
This setup uses the package documented for this task. Review its source and supported platforms before starting.
Save your machine in My Hardware to get an automatic starting choice. You can always choose any package yourself.
CURRENT SETUP
View weight source Qwen2.5 Coder · 7B · official
For the publisher's 4.7 GB Ollama text package at a short 4K context, we estimate at least 10 GB GPU memory or 16 GB Apple unified memory. For a more comfortable starting point, use 16 GB GPU memory or 24 GB unified memory. These are capacity estimates, not speed tests; longer context and other apps need additional headroom.
02
THE WORKFLOW
Set up Qwen2.5 Coder · 7B on your machine
Pick your operating system. Every command below is for the selected package and runtime.
Install Ollama for this operating system before running the model command.
Download and run Qwen2.5 Coder 7B
In your terminal, run the model. Ollama will automatically download the qwen2.5-coder:7b package (approximately 4.7 GB). After download, an interactive prompt appears where you can type coding requests.
ollama run qwen2.5-coder:7bAsk the model to write a quick sort algorithm
At the interactive prompt, type a request for code generation. For example: write a quick sort algorithm in Python with a brief explanation. Press Enter and wait for the streamed response.
Review the generated code
Inspect the model output in the terminal. Confirm that the response includes a complete Python quick sort implementation and a short explanation. Copy the code into a file such as quicksort.py and test it locally.
Exit the interactive session
When finished, type /bye or press Ctrl+D to exit the Ollama chat prompt.
03
SUCCESS CHECK · Qwen2.5 Coder · 7B
Run a small code result
Ask for a self-contained example, run it in a disposable file, and inspect the code and output before using it in a real project.
This is a source-linked setup, not a YouRunAI hardware test. Confirm your exact runtime version, package, and output before relying on it.
When it doesn’t go to plan
The ollama command is not found after installation.
Restart your terminal or command prompt so the PATH is refreshed. On macOS and Linux, you may need to start a new shell session. On Windows, reopen PowerShell or Command Prompt.
The model download is slow or stalls.
Ensure a stable internet connection. The qwen2.5-coder:7b package is approximately 4.7 GB. You can retry the ollama run qwen2.5-coder:7b command; Ollama resumes partial downloads.
Out of memory errors when loading the model.
Close other memory-intensive applications. The 7B model requires additional memory beyond the 4.7 GB package for runtime and context. If memory remains insufficient, use a smaller Qwen2.5 Coder variant from the Ollama library.
The model produces truncated or incomplete code.
Ask the model to continue or reduce the scope of the request. You can also start a new prompt with a more specific instruction, for example: provide the complete quick sort function only.
REFERENCE LIBRARY
4 SOURCESSources and files
Original instructions, model files, and compatibility notes behind this setup.
The model behind this workflow
Qwen2.5 Coder · 7BWill it run on your machine?
Save your machine to see a personalized rating and its reasoning.
Add my hardwareKeep exploring
Text
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