Update README.md

README.md

@@ -11,6 +11,6 @@ The algorithm is based on the assumption that two real numbers can be considered
 1) Provided a float vector []float64, use `CubeSet` and `CentralCube` functions to generate hypercube coordinates []int. The difference between the two functions is that one corresponds to hash-table record and the other to a query or vice versa, depending on performance/memory preference.
 2) `HashSet` and `DecimalHash`/`FNV1aHash` are used to get corresponding hash set and central hash from the hypercube coordinates above. There are 2 alternative hash functions: DecimalHash and FNV1aHash. DecimalHash does not have collisions, but is not suitable for cases with large number of buckets or dimensions. FNV1aHash is applicable for all cases.
 
-[Example](https://github.com/vitali-fedulov/imagehash/blob/master/hashes.go) for similar image search and clustering.
+[Example](https://github.com/vitali-fedulov/imagehash2/blob/main/hashes.go) for similar image search and clustering.
 
 [Go doc](https://pkg.go.dev/github.com/vitali-fedulov/hyper) for full code documentation.