Update README.md

README.md

@@ -3277,7 +3277,12 @@ license: cc-by-nc-4.0
 
 **SFR-Embedding by Salesforce Research.**
 
-The model is trained on top of [E5-mistral-7b-instruct](https://huggingface.co/intfloat/e5-mistral-7b-instruct) and [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1). The model has 32 layers and the embedding size is 4096.
+The model is trained on top of [E5-mistral-7b-instruct](https://huggingface.co/intfloat/e5-mistral-7b-instruct) and [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1).
+
+This project is for research purposes only. Third-party datasets may be subject to additional terms and conditions under their associated licenses. Please refer to specific papers for more details:
+- [MTEB benchmark](https://arxiv.org/abs/2210.07316)
+- [Mistral](https://arxiv.org/abs/2310.06825)
+- [E5-mistral-7b-instruct](https://arxiv.org/pdf/2401.00368.pdf)
 
 More technical details will be updated later.
 
@@ -3331,20 +3336,15 @@ scores = (embeddings[:2] @ embeddings[2:].T) * 100
 print(scores.tolist())
 ```
 
-Full MTEB evaluation will be added soon.
-
-SFR-Embedding Team
+Code for MTEB evaluation will be added soon.
 
+SFR-Embedding Team (∗indicates lead contributors).
 * Rui Meng*
 * Ye Liu*
 * Semih Yavuz
 * Yingbo Zhou
 * Caiming Xiong
 
-This project is for research purposes only. Third-party datasets may be subject to additional terms and conditions under their associated licenses. Please refer to specific papers for more details:
-- [E5 Dataset](https://arxiv.org/abs/2212.03533)
-- [MTEB Dataset](https://arxiv.org/abs/2210.07316)
-- [Mistral Dataset](https://arxiv.org/abs/2310.06825)