Summary
The video introduces LM Studio, a tool for running large language models locally to prioritize data privacy. The tutorial covers downloading LM Studio, selecting language models, using the chat interface, and Integration with Python applications. It demonstrates running multiple models simultaneously and discusses token generation speeds. Additionally, it shows how to run vision models like Lava 53 locally, offering a comprehensive guide for users.
Introduction to LM Studio
Introducing LM Studio and its capability to run large language models locally on a computer, ensuring data privacy. Overview of the beginner's tutorial and the latest updates, including running Vision models.
Downloading and Using LM Studio
Step-by-step guide on downloading LM Studio, selecting and downloading a large language model, using the chat interface, running multiple models simultaneously, and integrating with Python applications.
Running Multiple Models
Demonstration of running multiple models simultaneously, including loading and using different models in the LM Studio playground. Comparison of token generation speeds for different models.
Integrating Models with Applications
Instructions on integrating LM Studio models with custom applications using curl commands, starting a server, and streaming responses. Further demonstration with Python applications using OpenAI packages.
Running a Vision Model Locally
Guide on running a multimodal model specifically a vision model, such as Lava 53, locally on LM Studio. Steps include downloading model files, loading the model, uploading an image, and interpreting the model's description of the image.
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