Installation Guide for Code LLaMA 34b with Cloud GPU

👑 This video is about installing CodeLlama, a large language model for coding assistance.

🚀 The installation process focuses on setting up CodeLlama in a cloud GPU environment for running large versions of the model.

🔥 The video demonstrates the high performance of CodeLlama, which has outperformed GPT4 in open-source coding model evaluations.

🔑 Installing Code LLaMA 34b with a cloud GPU

💻 Deploying the template for text generation web UI

🌐 Connecting to the web UI through HTTP Service Port 7860

🔑 To install Code LLaMA 34b, you need to download the model from the blokes page and paste the model name in the text generation web UI for download.

📥 The download process may take some time as the model files are large, but once downloaded, you can select the model in the drop-down menu and choose the desired context window length.

🔍 Code LLaMA was trained on 16k context windows but can be fine-tuned up to 100K context windows.

🔧 The video demonstrates how to install Code LLaMA 34b with Cloud GPU.

⚙️ The parameters and settings for the model are discussed, including max new tokens and temperature.

📝 The video also shows how to use the prompt template to generate a code response and format it using Markdown.

🔑 Stopping the machine will save the downloaded files, but it will still incur charges; to avoid charges, terminate the machine.

🚀 Installing Code LLaMA 34b on a cloud GPU using run pod is fast and easy.

🔍 You can access and use even the largest unquantized models with this setup.