LightEmbed
/

sbert-all-MiniLM-L6-v2-onnx

@@ -8,7 +8,7 @@ tags:
 ---
-# sbert-all-MiniLM-L6-v2-onnx
 This is the ONNX version of the Sentence Transformers model sentence-transformers/all-MiniLM-L6-v2 for sentence embedding, optimized for speed and lightweight performance. By utilizing onnxruntime and tokenizers instead of heavier libraries like sentence-transformers and transformers, this version ensures a smaller library size and faster execution. Below are the details of the model:
 - Base model: sentence-transformers/all-MiniLM-L6-v2
@@ -47,7 +47,7 @@ Then you can use the model using onnx model name like this:
 from light_embed import TextEmbedding
 sentences = ["This is an example sentence", "Each sentence is converted"]
-model = TextEmbedding('sbert-all-MiniLM-L6-v2-onnx')
 embeddings = model.encode(sentences)
 print(embeddings)
 ```

 ---
+# LightEmbed/sbert-all-MiniLM-L6-v2-onnx
 This is the ONNX version of the Sentence Transformers model sentence-transformers/all-MiniLM-L6-v2 for sentence embedding, optimized for speed and lightweight performance. By utilizing onnxruntime and tokenizers instead of heavier libraries like sentence-transformers and transformers, this version ensures a smaller library size and faster execution. Below are the details of the model:
 - Base model: sentence-transformers/all-MiniLM-L6-v2
 from light_embed import TextEmbedding
 sentences = ["This is an example sentence", "Each sentence is converted"]
+model = TextEmbedding('LightEmbed/sbert-all-MiniLM-L6-v2-onnx')
 embeddings = model.encode(sentences)
 print(embeddings)
 ```