Update README.md

README.md

@@ -19,8 +19,6 @@ library_name: transformers
 ### Description:
 `llama-embed-nemotron-8b` is a versatile text embedding model trained by NVIDIA and optimized for retrieval, reranking, semantic similarity, and classification use cases. This model has robust capabilities for multilingual and cross-lingual text retrieval. It is designed to serve as a foundational component in text-based Retrieval-Augmented Generation (RAG) systems.
 
-This model achieves state-of-the-art performance on the [multilingual MTEB leaderboard](https://huggingface.co/spaces/mteb/leaderboard) (as of October 23, 2025).
-
 This model is for non-commercial/research use only.
 
 ### License/Terms of Use
@@ -242,20 +240,6 @@ We test the model on 131 tasks from [MMTEB: Massive Multilingual Text Embedding
 - Number of task types: 9
 - Number of domains: 20 <br>
 
-**MMTEB Leaderboard Benchmark Ranking** <br>
-
-Below we present results for `MTEB(Multilingual, v2)` split of MMTEB benchmark (as of October 23, 2025). Ranking on MMTEB Leaderboards is performed based on the Borda rank. Each task is treated as a preference voter, which gives votes on the models per their relative performance on the task. The best model obtains the highest number of votes. The model with the highest number of votes across tasks obtains the highest rank. The Borda rank tends to prefer models that perform well broadly across tasks.
-
-| Borda Rank | Model | Borda Votes | Mean (Task) |
-|-------|-------|---------------------|---------------------|
-| **1.** | llama-embed-nemotron-8b | **39,573** | 69.46 |
-| 2. | gemini-embedding-001      |         39,368            |         68.37            |
-| 3. | Qwen3-Embedding-8B      |         39,364            |         **70.58**            |
-| 4. | Qwen3-Embedding-4B      |         39,099           |         69.45            |
-| 5. | Qwen3-Embedding-0.6B      |         37,419            |         64.34            |
-| 6. | gte-Qwen2-7B-instruct | 37,167 | 62.51 |
-| 7. | Linq-Embed-Mistral |  37,149 | 61.47 |
-
 **Data Collection Method by dataset:**
 * Hybrid: Automated, Human, Synthetic<br>