Run open large language models like Gemma, Llama or DeepSeek locally to perform AI inference on consumer hardware.
InstructorMaximilian SchwarzmüllerInstruction covers essential technical concepts including Modelfiles, GGUF files, and parameter configuration within Ollama.
The curriculum includes methods for integrating local models into applications using Python and JavaScript SDKs and OpenAI-compatible APIs.
Editorial course preview
These 4 complementary views highlight concrete, legible examples from the course presentation.
A dark-themed software interface displaying a model search list and a detailed download panel for a Gemma 3 27B QAT model.
A dark-themed LM Studio interface displaying a chat window with a PDF attachment and a user prompt to summarize a financial report.
A dark-themed LM Studio interface displaying a chat session where a local model extracts merchant, location, and date details from an uploaded receipt image.
A dark-mode chat interface displaying a text response about open LLM benefits, including bullet points and a bottom input bar with action buttons
Learner signals suggest that screenshots and specific feature locations in LM Studio and Ollama may no longer align with current software versions.
The content aligns with the target of beginner and tech-enthusiast users, though some advanced hardware topics are missing.
