Update README.md

README.md

@@ -3593,7 +3593,7 @@ model-index:
   <img src="images/gme_logo.png" alt="GME Logo" style="width: 100%; max-width: 450px;">
 </p>
 
-<p align="center"><b>GME: General Multimodal Embeddings</b></p>
+<p align="center"><b>GME: General Multimodal Embedding</b></p>
 
 ## GME-Qwen2-VL-2B
 
@@ -3619,15 +3619,11 @@ The `GME` models support three types of input: **text**, **image**, and **image-
 ## Model List
 | Models | Model Size | Max Seq. Length | Dimension | MTEB-en| UMRB |
 |:-----: | :-----: |:-----: |:-----: |:-----: | :-----: |
-|[`gme-Qwen2VL-2B`](https://huggingface.co/Alibaba-NLP/gme-Qwen2-VL-2B-Instruct) | 2.21B | 32768 | 1536 | - | 64.45 |
-|[`gme-Qwen2VL-7B`](https://huggingface.co/Alibaba-NLP/gme-Qwen2-VL-7B-Instruct) | 8.29B | 32768 | 3584 | - | 67.02 |
+|[`gme-Qwen2-VL-2B`](https://huggingface.co/Alibaba-NLP/gme-Qwen2-VL-2B-Instruct) | 2.21B | 32768 | 1536 | - | 64.45 |
+|[`gme-Qwen2-VL-7B`](https://huggingface.co/Alibaba-NLP/gme-Qwen2-VL-7B-Instruct) | 8.29B | 32768 | 3584 | - | 67.44 |
 
 ## Usage 
-**Use Transformers**
 ```
-
-```
-
 **Use with custom code**
 
 ```python
@@ -3677,8 +3673,8 @@ We validated the performance on our universal multimodal retrieval benchmark (**
 | One-Peace          | 4B   | 43.54        | 31.27     | 61.38       | 42.9        | 65.59     | 42.72       | 28.29      | 6.73       | 23.41       | 42.03      |
 | DSE                | 4.2B | 48.94        | 27.92     | 40.75       | 78.21       | 52.54     | 49.62       | 35.44      | 8.36       | 40.18       | 50.63      |
 | E5-V               | 8.4B | 52.41        | 27.36     | 46.56       | 41.22       | 47.95     | 54.13       | 32.9       | 23.17      | 7.23        | 42.48      |
-| **GME-Qwen2-VL-2B** | 2.2B | 55.93 | 29.86	| 57.36	| 87.84	| **61.93** |	76.47	| 64.58	 | 37.02	| 66.47 | 64.45 |
-| **GME-Qwen2-VL-7B** | 8.3B | **58.19** | 31.89 | **61.35** | **89.92** | 60.83 | **80.94** | **66.18** | **42.56** | **73.62** | **67.02** |
+| **[GME-Qwen2-VL-2B](https://huggingface.co/Alibaba-NLP/gme-Qwen2-VL-2B-Instruct)** | 2.2B | 55.93 | 29.86	| 57.36	| 87.84	| 61.93 |	76.47	| 64.58	 | 37.02	| 66.47 | 64.45 |
+| **[GME-Qwen2-VL-7B](https://huggingface.co/Alibaba-NLP/gme-Qwen2-VL-7B-Instruct)** | 8.3B | **58.19** | 31.89 | **61.35** | **89.92** | **65.83** | **80.94** | **66.18** | **42.56** | **73.62** | **67.44** |
 
 The [MTEB Leaderboard](https://huggingface.co/spaces/mteb/leaderboard) English tab shows the text embeddings performence of our model.
 
@@ -3693,7 +3689,6 @@ Due to the lack of relevant data, our models and evaluations retain one single i
 
 We will extend to multi-image input, image-text interleaved data as well as multilingual data in the future version.
 
-
 ## Redistribution and Use
 
 We encourage and value diverse applications of GME models and continuous enhancements to the models themselves.
@@ -3704,12 +3699,19 @@ We encourage and value diverse applications of GME models and continuous enhance
 
 ## Cloud API Services
 
-In addition to the open-source [GME](https://huggingface.co/collections/Alibaba-NLP/gme-models) series models, GME series models are also available as commercial API services on Alibaba Cloud.
+In addition to the open-source [GME](https://huggingface.co/collections/Alibaba-NLP/gme-models-67667e092da3491f630964d6) series models, GME series models are also available as commercial API services on Alibaba Cloud.
 
 - [MultiModal Embedding Models](https://help.aliyun.com/zh/model-studio/developer-reference/general-text-embedding/): The `multimodal-embedding-v1` model service is available.
 
 Note that the models behind the commercial APIs are not entirely identical to the open-source models.
 
+## Hiring
+
+We have open positions for Research Interns and Full-Time Researchers to join our team at Tongyi Lab. 
+We are seeking passionate individuals with expertise in representation learning, LLM-driven information retrieval, Retrieval-Augmented Generation (RAG), and agent-based systems. 
+Our team is located in the vibrant cities of Beijing and Hangzhou, offering a collaborative and dynamic work environment where you can contribute to cutting-edge advancements in artificial intelligence and machine learning.
+If you are driven by curiosity and eager to make a meaningful impact through your work, we would love to hear from you. Please submit your resume along with a brief introduction to <a href="mailto:[email protected]">[email protected]</a>.
+
 ## Citation
 If you find our paper or models helpful, please consider cite: