Update README.md

README.md

@@ -24,11 +24,7 @@ The **gte-multilingual-base** model is the latest in the [GTE](https://huggingfa
 - Embedding Dimension: 768
 - Max Input Tokens: 8192
 
-## Requirements
-```
-transformers>=4.39.2
-flash_attn>=2.5.6
-```
+
 ## Usage 
 
 Get Dense Embeddings with Transformers
@@ -104,4 +100,17 @@ hybird_scores = model.compute_scores(pairs, dense_weight=1.0, sparse_weight=0.3)
 print('dense_scores', dense_scores)
 print('sparse_scores', sparse_scores)
 print('hybird_scores', hybird_scores)
+```
+
+## Citation
+```
+@misc{zhang2024mgtegeneralizedlongcontexttext,
+      title={mGTE: Generalized Long-Context Text Representation and Reranking Models for Multilingual Text Retrieval}, 
+      author={Xin Zhang and Yanzhao Zhang and Dingkun Long and Wen Xie and Ziqi Dai and Jialong Tang and Huan Lin and Baosong Yang and Pengjun Xie and Fei Huang and Meishan Zhang and Wenjie Li and Min Zhang},
+      year={2024},
+      eprint={2407.19669},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2407.19669}, 
+}
 ```