python setup.py build_ext --inplace Notebooks IBM.ipynb aims to reproduce the results in Figure 3 of the IBM paper. Round Analysis.ipynb takes a closer look at the parity check matrix, explains the basic concept of sliding window decoding and show how the windows are extracted. Sliding W...
the rope still receives the absolute positions of the tokens, but the data is actually stored in the position pos % sliding_window. But maybe I am misunderstanding something, can you point me to the specific code? Member ggerganov Jul 1, 2024 Yes, it should be possible. The thing I ...
The basic concept of a sliding window analysis is to group variants located near each other, in either 1D or 3D space, into one unit and analyze them together to improve power, much like a gene-based collapsing analysis but at a more localized scale. Rather than size our sliding window by...
DIP - Concept of Dithering DIP - Histograms Introduction DIP - Brightness and Contrast DIP - Image Transformations DIP - Histogram Sliding DIP - Histogram Stretching DIP - Introduction to Probability DIP - Histogram Equalization DIP - Gray Level Transformations DIP - Concept of convolution DIP - Conc...
As a concept, latent keyframes achieve the same affect as a uniform mask with the chosen strength value. Nodes The ControlNet nodes provided here are the Apply Advanced ControlNet and Load Advanced ControlNet Model (or diff) nodes. The vanilla ControlNet nodes are also compatible, and can be...
My understanding is that the mask would be the same for all the layers, and it relies on the fact that the states in the KV cache depend on all the previous tokens to be able to access information beyond the sliding window. Collaborator Author ngxson Jul 1, 2024 I looked deeper into...
Anomaly detection and a data imputation are necessary steps in a data monitoring system. Anomaly data can be detected if its values lie outside of a normal pattern distribution. We developed a median-based statistical outlier detection approach using a sliding window technique. In order to fill ...
Anomaly detection and a data imputation are necessary steps in a data monitoring system. Anomaly data can be detected if its values lie outside of a normal pattern distribution. We developed a median-based statistical outlier detection approach using a sliding window technique. In order to fill ...