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Co-authored-by: nerda-codes <[email protected]>

Author: bene2k1

ai-data/managed-inference/reference-content/bge-multilingual-gemma2.mdx

@@ -7,6 +7,9 @@ content:
   paragraph: This page provides information on the BGE-Multilingual-Gemma2 embedding model
 tags: embedding
 categories:
+dates:
+  validation: 2024-10-30
+  posted: 2024-10-30
   - ai-data
 ---
 
@@ -37,7 +40,7 @@ As such, it is distributed under the [Gemma terms of use](https://ai.google.dev/
 
 ## Why is it useful?
 
-- BGE-Multilingual-Gemma2 tops the [MTEB leaderboard](https://huggingface.co/spaces/mteb/leaderboard) scoring #1 in french, #1 in polish, #7 in english, as of writing (Q4 2024).
+- BGE-Multilingual-Gemma2 tops the [MTEB leaderboard](https://huggingface.co/spaces/mteb/leaderboard) scoring the number one spot in French and Polish, and number seven in English, at the time of writing this page (Q4 2024).
 - As its name suggests, the model's training data spans a broad range of languages, including English, Chinese, Polish, French, and more!
 - It encodes text into 3584-dimensional vectors, providing a very detailed representation of sentence semantics.
 - BGE-Multilingual-Gemma2 in its L4/FP32 configuration boats a high context length of 4096 tokens, particularly useful for ingesting data and building RAG applications.