How To Install Code LLaMA 34b 👑 With Cloud GPU (Huge Model, Incredible Performance)
AI Summary
Summary: Installing CodeLama on a Cloud GPU with RunPod
- Introduction
- Demonstrating installation of CodeLama, a coding assistant by Meta.
- CodeLama is based on LLaMA2 and outperformed GPT-4 in tests.
- Installation Steps
- Choose the Blokes Wizard Coder Python 13B v1.0 quantized version for installation.
- Sign up for a RunPod account at runpod.io.
- Select a GPU, such as the RTX A6000 with 48GB VRAM at $0.79/hr.
- Deploy using the “Bloke Local LLM’s One-Click UI” template for easy setup.
- After deployment, connect to the service at Port 7860.
- Download the desired model from the Blokes page and paste it into the web UI.
- Refresh the UI to load the model and select it from the dropdown.
- Adjust settings like max sequence length and temperature for code generation.
- Use the prompt template to input instructions and generate code.
- Render the output in Markdown if needed.
- Finalizing
- Stop the cloud service when done to avoid extra charges.
- Terminate the instance completely to prevent any charges.
- Conclusion
- The process is fast and simple, allowing access to large, even unquantized, models.
- Encourages likes and subscriptions for the video tutorial.