In this tutorial, we’ll walk you through the process of setting up and using Ollama for private model inference on a VM with GPU, either on your local machine or a rented VM from Vast.ai or Runpod.io. Ollama allows you to run models privately, ensuring data security and faster inference times thanks to the power of GPUs. By leveraging a GPU-powered VM, you can significantly improve the performance and efficiency of your model inference tasks.
Outline
- Set up a VM with GPU on Vast.ai
- Start Jupyter Terminal
- Install Ollama
- Run Ollama Serve
- Test Ollama with a model
- (Optional) using your own model
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Setting Up a VM with GPU on Vast.ai
1. Create a VM with GPU: — Visit Vast.ai to create your VM. — Choose a VM with at least 30 GB of storage to accommodate the models. This ensures you have enough space for installation and model storage. — Select a VM that costs less than $0.30 per hour to keep the setup cost-effective.
