Researchers from the University of Maryland, Lawrence Livermore, Columbia and TogetherAI have developed a training technique that triples LLM inference speed without auxiliary models or infrastructure ...
XDA Developers on MSN
I started using my local LLM with Obsidian and should have done it sooner
Obsidian is already great, but my local LLM makes it better ...
Use the vitals package with ellmer to evaluate and compare the accuracy of LLMs, including writing evals to test local models ...
The company open-sourced an 8 billion parameter LLM, Steerling-8B, trained with a new architecture designed to make its ...
The new lineup includes 30-billion and 105-billion parameter models; a text-to-speech model; a speech-to-text model; and a vision model to parse documents.
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