![]() The code is reasonably short, and the Writing a plugin to support a new model tutorial should provide all of the information anyone familiar with Python needs to start hacking on this (or a new) plugin. What are the most interesting models to try this out with? The download-model command is designed to support experimentation here.Figuring these out would be very valuable. There are all sorts of llama-cpp-python options that might be relevant for getting better performance out of different models.Does it work on Linux and Windows? It should do, but I’ve not tried it yet. One (Mac) Security Agent Audacity The Audacity Team - Implement Run for Audacity Sentinel Agent.I’m not yet sure that this is using the GPU on my Mac-it’s possible that alternative installation mechanisms for the llama-cpp-python package could help here, which is one of the reasons I made that a separate step rather than depending directly on that package.How to speed this up-right now my Llama prompts often take 20+ seconds to complete.I would welcome contributions that explore any of the following areas: ![]() I only just got this working-there’s a lot of room for improvement. Open questions and potential improvements Note that this particular model is a completion model, so the prompts you send it need to be designed to produce good results if used as the first part of a sentence. ' is that they can spray their scent up to 10 feet.' model.prompt( "A fun fact about skunks ").text() ![]()
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