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[example] Don't always normalize the embeddings in clustering example #2520

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Mar 1, 2024
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[example] Don't always normalize the embeddings in clustering example #2520

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5 changes: 2 additions & 3 deletions examples/applications/clustering/agglomerative.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,6 @@

from sentence_transformers import SentenceTransformer
from sklearn.cluster import AgglomerativeClustering
import numpy as np

embedder = SentenceTransformer("all-MiniLM-L6-v2")

Expand All @@ -26,8 +25,8 @@
]
corpus_embeddings = embedder.encode(corpus)

# Normalize the embeddings to unit length
corpus_embeddings = corpus_embeddings / np.linalg.norm(corpus_embeddings, axis=1, keepdims=True)
# Some models don't automatically normalize the embeddings, in which case you should normalize the embeddings:
# corpus_embeddings = corpus_embeddings / np.linalg.norm(corpus_embeddings, axis=1, keepdims=True)

# Perform kmean clustering
clustering_model = AgglomerativeClustering(
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