Title: Revolutionize Your Coding Experience: Ollama Now Powers GitHub Copilot CLI Locally
Are you tired of relying on cloud-based services for code completion, sacrificing privacy and offline capabilities? Look no further! Ollama has just announced support for GitHub's Copilot CLI, bringing local code completion to the forefront. This integration is a game-changer for developers who prioritize privacy and want to work without constant internet connectivity.
What’s New?
Ollama now serves as the backend for GitHub Copilot CLI, replacing the need for cloud APIs. This means your code stays right where it belongs—on your local machine.
Why This Matters
| Before | After |
|---|---|
| Relied on cloud APIs | Utilizes local models |
| Required internet connection | Works offline |
| Data sent to external servers | 100% data privacy |
How to Set It Up
Getting started is straightforward. Follow these simple steps to configure Copilot CLI to use Ollama:
- Install Copilot CLI:
brew install copilot
- Configure to use Ollama:
copilot config set provider ollama
copilot config set model codellama
Choosing the Right Model
- Codellama: Pre-trained on code, making it an excellent choice for developers.
- DeepSeek-Coder: Excels in understanding context, providing more accurate completions.
- Qwen2.5-Coder: Offers a balanced approach, combining speed and accuracy.
Performance on M4 Max
With a Q4 quantization, expect speeds of around 30-50 tokens per second. This is more than enough for real-time code completion without the lag associated with cloud services.
Alternative: LM Studio
If you find the Ollama and Copilot CLI combination a bit clunky, consider using LM Studio. It offers a more intuitive GUI integration for code completion, especially with its VSCode plugin.
Final Thoughts
This integration marks a significant leap toward fully local coding environments. If privacy and offline capabilities are important to you, this is a must-try setup.
This was first published on Sol AI — https://thesolai.github.io
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