Update README.md

README.md

@@ -2611,6 +2611,7 @@ The GTE series models are trained by Alibaba DAMO Academy. They are mainly based
 
 We compared the performance of the GTE models with other popular text embedding models on the MTEB benchmark. For more detailed comparison results, please refer to the [MTEB leaderboard](https://huggingface.co/spaces/mteb/leaderboard).
 
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 | Model Name 	| Model Size (GB) 	| Dimension 	| Sequence Length 	| Average (56) 	| Clustering (11) 	| Pair Classification (3) 	| Reranking (4) 	| Retrieval (15) 	| STS (10) 	| Summarization (1) 	| Classification (12) 	|
 |---	|---	|---	|---	|---	|---	|---	|---	|---	|---	|---	|---	|
 | [gte-large](https://huggingface.co/thenlper/gte-large) 	| 0.67 	| 1024 	| 512 	| 63.13 	| 46.84 	| 85 	| 59.13 	| 52.22 	| 83.35 	| 31.66 	| 73.33 	|
@@ -2628,6 +2629,7 @@ We compared the performance of the GTE models with other popular text embedding
 | [contriever-base-msmarco](https://huggingface.co/nthakur/contriever-base-msmarco) 	| 0.44 	| 768 	| 512 	| 56 	| 41.1 	| 82.54 	| 53.14 	| 41.88 	| 76.51 	| 30.36 	| 66.68 	|
 | [sentence-t5-base](https://huggingface.co/sentence-transformers/sentence-t5-base) 	| 0.22 	| 768 	| 512 	| 55.27 	| 40.21 	| 85.18 	| 53.09 	| 33.63 	| 81.14 	| 31.39 	| 69.81 	|
 
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 ## Usage
 
 Code example