Update README.md

README.md

@@ -50,7 +50,7 @@ I've been asked what this is.  For each layer, I use mergekit io to extract each
 
 * Recursive Pairwise Disjoint: Using this information I build a stack of layer deltas.  I'm a little compute limited, so I treat them in pairs.  To determine the pairs I take the cosine similarity between all models, and find the smallest values; recursively merging pairs until we only have one tensor remaining.
 * Normalized: I take and divide each layer by it's norm, and then scale back up by multiplying the result by a midpoint from the norms of the tensors.
-* Denoised Fourier Interpolation: I first treat the tensor to a 2d fourier transform; then merge the tensors using SLERP or addition; then zero out the weights below a threshold percentage (a somewhat high 2%, but remains coherent all the way to 100%).
+* Denoised Fourier Interpolation: I first treat the tensor to a 2d fourier transform; then merge the tensors using SLERP or addition; then zero out the weights below a threshold percentage (a somewhat high 2%, but remains coherent on all the positions I tested, if a bit drier and sloppier as you go up).
 
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