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Something in Privacy Badger's behavior changed recently. A Streamable CDN address cdn-cf-east.streamable.com had the slider all the way to the left/red side. Set it to "No Cookies"/yellow in the middle and they started working again.


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I would like to transform xml files in below structure to another one pretty similar to this, let's say each element name changes (ie A..F -> ANew..FNew). I would like to do it in streamable mode introduced by XSLT 3.0 using Saxon-EE v9.7 since I need to process very big files. Although I can partially succeed it (Root/Head section), I could not come up with a solution totally address the whole document since I cannot meet streamability rules Saxon-EE applies and I am lost among them... I appreciate any xslt suggestion that would work in streaming mode with Saxon-EE v9.7.

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As this datasets needs 134GB of disk space to load I thought the streaming feature of load_dataset would come handy here but apparently streaming is not possible on Natural Questions. It was my assumption that all datasets were streamable on huggingface. Was my assumption incorrect?

Neural fields have emerged as a new data representation paradigm and have shown remarkable success in various signal representations. Since they preserve signals in their network parameters, the data transfer by sending and receiving the entire model parameters prevents this emerging technology from being used in many practical scenarios. We propose streamable neural fields, a single model that consists of executable sub-networks of various widths. The proposed architectural and training techniques enable a single network to be streamable over time and reconstruct different qualities and parts of signals. For example, a smaller sub-network produces smooth and low-frequency signals, while a larger sub-network can represent fine details. Experimental results have shown the effectiveness of our method in various domains, such as 2D images, videos, and 3D signed distance functions. Finally, we demonstrate that our proposed method improves training stability, by exploiting parameter sharing. ff782bc1db

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