Create Private GPU-Accelerated Llama Copilot in Visual Studio Code extension for Enhanced Code Generation
Step-by-step guide to setting up your local system
1. Ensure GPU with at least 4GB configuration:
- Make sure your system has at least a GPU with 4GB of VRAM, else you will get a lot of late response.
2. Install CUDA Toolkit and cuDNN:
- Install CUDA Toolkit ( Systrem level GPU Driver) and cuDNN (Run time driver ) for GPU support. You can download them from the NVIDIA website and follow the installation instructions.
3. Install Visual Studio Code:
- Download and install Visual Studio Code from the official website.
4. Install Ollama:
- Open your terminal and run the following command to install Ollama:
curl https://ollama.ai/install.sh | sh
5. Download the Llama3 model:
- After installing Ollama, download the Llama3 model with 8 billion parameters.
ollama run llama3:8b
6. Configure Ollama in VS Code:
- Open Visual Studio Code.
- Install the CodeGPT: Chat & AI Agents extension store.
领英推荐
7. CodeGPT: Chat & AI Agents settings:
- Change the AI provider and select Ollama
- Next, Change Code GPT.Autocomplete: Provider and select
llama3:instruct
7. Start using Ollama in VS Code:
A private copilot is ready for you in your system.
Features are the following:
Ensure your workspace remains private; while ChatGPT interactions are typically public, you can now keep them confidential within your system.