cl-nagoya
/

ruri-pt-base

Sentence Similarity

sentence-transformers

feature-extraction

Inference Endpoints

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hpprc commited on Sep 13

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@@ -16,11 +16,8 @@ datasets:
 # Ruri: Japanese General Text Embeddings
 ## Usage
-### Direct Usage (Sentence Transformers)
 First install the Sentence Transformers library:
 ```bash
@@ -45,7 +42,7 @@ sentences = [
 embeddings = model.encode(sentences, convert_to_tensor=True)
 print(embeddings.size())
-# [4, 1024]
 similarities = F.cosine_similarity(embeddings.unsqueeze(0), embeddings.unsqueeze(1), dim=2)
 print(similarities)

 # Ruri: Japanese General Text Embeddings
 ## Usage
 First install the Sentence Transformers library:
 ```bash
 embeddings = model.encode(sentences, convert_to_tensor=True)
 print(embeddings.size())
+# [4, 768]
 similarities = F.cosine_similarity(embeddings.unsqueeze(0), embeddings.unsqueeze(1), dim=2)
 print(similarities)