{{< blurhash
  src="comfyui/UNetSelfAttentionMultiply.png"
  blurhash="L5N1WJE201t7^kIoQ.xa0yRk-Bt7"
  width="975"
  height="575"
  alt="This is a digital screenshot of an online tool interface specifically designed to calculate model accuracy based on performance metrics such as k-fold cross-validation (k) variance (v) and out-of-sample error (1 - MSE). The background features a light grey grid pattern with pink lines forming geometric shapes at various angles. The top part of the interface displays text indicating "#393 #BETA!" followed by two small emojis resembling orange fox-like faces. Below that there's another line reading "UNetSelfAttentionMultiplay " suggesting it’s from a project or paper title. In the center-left section labeled “model ” three options are provided: - q : representing quadratic loss function. - v : representing variance. - k : representing k-fold cross-validation method. To the right of these labels are input fields where users can enter numerical values. For instance - r = 9 allows you to set the number of quadratics used during training. - 1.0 = represents the first value for each metric type within the range specified. - 10.0 represents the tenth value in the sequence. - 100.0 represents the hundredth value in the sequence. Each field has a corresponding button labeled 'out ' which likely triggers calculations when clicked. At the bottom left corner a red dot icon indicates some form of alert or notification. Overall the design is clean and functional typical of web-based tools focused on statistical analysis and data modeling."
  grid="true"
>}}