Run personalized LLM fashions in your system privately | Use ChatGPT like interface | Construct native purposes utilizing Python
What you’ll be taught
Set up and configure Ollama in your native system to run giant language fashions privately.
Customise LLM fashions to swimsuit particular wants utilizing Ollama’s choices and command-line instruments.
Execute all terminal instructions vital to manage, monitor, and troubleshoot Ollama fashions
Arrange and handle a ChatGPT-like interface utilizing Open WebUI, permitting you to work together with fashions domestically
Deploy Docker and Open WebUI for operating, customizing, and sharing LLM fashions in a non-public setting.
Make the most of totally different mannequin varieties, together with textual content, imaginative and prescient, and code-generating fashions, for varied purposes.
Create customized LLM fashions from a gguf file and combine them into your purposes.
Construct Python purposes that interface with Ollama fashions utilizing its native library and OpenAI API compatibility.
Develop a RAG (Retrieval-Augmented Technology) utility by integrating Ollama fashions with LangChain.
Implement instruments and brokers to boost mannequin interactions in each Open WebUI and LangChain environments for superior workflows.
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