Knowledge Base Resources
These resources have been contributed and “vetted” by the community of cyberinfrastructure professionals (researchers, research computing facilitators, research software engineers and HPC system administrators) that are participating in programs such as this one, that are supported by the ConnectCI community management platform. Additional Knowledge Base Resources are always welcome!
Fine-tuning LLMs with PEFT and LoRA
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As LLMs get larger fine-tuning to the full extent can become difficult to train on consumer hardware. Storing and deploying these tuned models can also be quite expensive and difficult to store. With PEFT (parameter -efficent fine tuning), it approaches fine-tune on a smaller scale of model parameters while freezing most parameters of the pretrained LLMs. Basically it is providing full performance that which is similar if not better than full fine tuning while only having a small number of trainable parameters. This source explains that as well as going over LORA diagrams and a code walk through.
UCLA Extended Reality (XR) collaboration resources and Workshop
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Comprehensive Extended Reality (XR) collaboration resources for building a high performance extended reality (XR), augmented reality (AR), virtual reality (VR) and mixed reality campus teams. The tags set are a small subset of the the topics covered.
Astronomy data analysis with astropy
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Astropy is a community-driven package that offers core functionalities needed for astrophysical computations and data analysis. From coordinate transformations to time and date handling, unit conversions, and cosmological calculations, Astropy ensures that astronomers can focus on their research without getting bogged down by the intricacies of programming. This guide walks you through practical usage of astropy from CCD data reduction to computing galactic orbits of stars.