Update README.md

README.md

@@ -6,40 +6,40 @@ language:
 - en
 ---
 
-# <b>AceGPT</b>
+# <b>MgGPT</b>
 
-AceGPT is a fully fine-tuned generative text model collection, particularly focused on the Arabic language domain. 
+MgGPT is a fully fine-tuned generative text model collection, particularly focused on the Arabic language domain. 
 This is the repository for the version 2 of the 70B pre-trained model, developed based on [Meta-Llama-3-70B](https://huggingface.co/meta-llama/Meta-Llama-3-70B).
 
 ---
 ## Model Details
-We have released the AceGPT family of large language models, which is a collection of fully fine-tuned generative text models, ranging from 7B to 70B parameters. Our models include two main categories: AceGPT and AceGPT-chat. AceGPT-chat is an optimized version specifically designed for dialogue applications. It is worth mentioning that our models have demonstrated superior performance compared to all currently available open-source Arabic dialogue models in multiple benchmark tests. Furthermore, in our human evaluations, our models have shown comparable satisfaction levels to some closed-source models, such as ChatGPT, in the Arabic language.
+We have released the MgGPT family of large language models, which is a collection of fully fine-tuned generative text models, ranging from 8B to 70B parameters. Our models include two main categories: AceGPT and AceGPT-chat. AceGPT-chat is an optimized version specifically designed for dialogue applications. It is worth mentioning that our models have demonstrated superior performance compared to all currently available open-source Arabic dialogue models in multiple benchmark tests. Furthermore, in our human evaluations, our models have shown comparable satisfaction levels to some closed-source models, such as ChatGPT, in the Arabic language.
 ## Model Developers 
 We are from the King Abdullah University of Science and Technology (KAUST), the Chinese University of Hong Kong, Shenzhen (CUHKSZ) and the Shenzhen Research Institute of Big Data (SRIBD).
 ## Variations
-AceGPT families come in a range of parameter sizes —— 7B, 8B, 13B, 32B and 70B, each size of model has a base category and a -chat category.
-## Paper
-The paper can be accessed at [link](https://huggingface.co/FreedomIntelligence/AceGPT-v2-70B-Chat/blob/main/Alignment_at_Pre_training__a_Case_Study_of_Aligning_LLMs_in_Arabic.pdf).
+MgGPT families come in a range of parameter sizes —— 8B, 13B, 32B and 70B, each size of model has a base category and a -chat category.
+<!-- ## Paper -->
+<!-- The paper can be accessed at [link](https://huggingface.co/FreedomIntelligence/AceGPT-v2-70B-Chat/blob/main/Alignment_at_Pre_training__a_Case_Study_of_Aligning_LLMs_in_Arabic.pdf). -->
 ## Input 
 Models input text only.
 ## Output
 Models output text only.
 ## Model Evaluation Results
 
-Arabic Benchmark evaluations on [Arabic MMLU](https://github.com/FreedomIntelligence/AceGPT) are conducted using accuracy scores as metrics, following the evaluation framework available at https://github.com/FreedomIntelligence/AceGPT/tree/main. 
+<!-- Arabic Benchmark evaluations on [Arabic MMLU](https://github.com/FreedomIntelligence/AceGPT) are conducted using accuracy scores as metrics, following the evaluation framework available at https://github.com/FreedomIntelligence/AceGPT/tree/main.  -->
 
 |             | Arabic-trans MMLU | ArabicMMLU (koto et al.) | Arabic EXAMS | Arabic ACVA clean | Arabic ACVA all | Arabic AraTrust | Arabic ARC-C | Arabic Avg.  |
 | ----------------- | :-----------------: | :------------------------: | :------------: | :-----------------: | :---------------: | :---------------: | :------------: | :------------: |
 | Qwen1.5-7B        | 42.14             | 46.41                    | 38.34        | 75.17             | 75.88           | 54.21           | 45.56        | 53.96        |
 | Jais-30B-v3       | 43.42             | 44.47                    | 45.78        | 83.39             | 79.51           | 62.64           | 45.56        | 57.82        |
 | Llama3-8B         | 47.22             | 45.78                    | 46.34        | 77.49             | 76.68           | 67.82           | 47.53        | 58.41        |
-| **AceGPT-v2-8B**  | 48.41             | 50.17                    | 46.15        | 80.14             | 78.84           | 65.90           | 49.91        | 59.93        |
+| **MgGPT-8B**  | 48.41             | 50.17                    | 46.15        | 80.14             | 78.84           | 65.90           | 49.91        | 59.93        |
 | ChatGPT 3.5 Turbo | 49.07             | 57.70                    | 45.93        | 74.45             | 76.88           | 65.13           | 60.24        | 61.34        |
 | Qwen1.5-32B       | 55.90             | 55.94                    | 52.84        | 78.91             | 80.07           | 69.34           | 67.66        | 65.81        |
 | Qwen1.5-72B       | 60.24             | 61.23                    | 54.41        | 82.98             | <u>81.20</u>    | 75.93           | 76.79        | 70.40        |
-| **AceGPT-v2-32B** | 58.71             | 65.67                    | 52.74        | 82.66             | 81.04           | 80.46           | 71.69        | 70.42        |
+| **MgGPT-32B** | 58.71             | 65.67                    | 52.74        | 82.66             | 81.04           | 80.46           | 71.69        | 70.42        |
 | Llama3-70B        | <u>65.16</u>      | 65.67                    | 54.78        | 83.48             | **82.92**       | 74.84           | 77.30        | 72.02        |
-| **AceGPT-v2-70B** | **65.19**         | <u>67.71</u>             | <u>56.19</u> | **84.79**         | 80.93           | <u>80.93</u>    | <u>80.93</u> | <u>73.81</u> |
+| **MgGPT-70B** | **65.19**         | <u>67.71</u>             | <u>56.19</u> | **84.79**         | 80.93           | <u>80.93</u>    | <u>80.93</u> | <u>73.81</u> |
 | GPT-4             | 65.06             | **72.50**                | **57.76**    | <u>84.06</u>      | 79.43           | **90.04**       | **85.67**    | **76.36**    |
 
 Benchmarks for English and Chinese are conducted using the [OpenCompass](https://github.com/open-compass/OpenCompass/) framework.
@@ -47,15 +47,15 @@ Benchmarks for English and Chinese are conducted using the [OpenCompass](https:/
 |             | MMLU | RACE | English Avg. | CMMLU | CEval | Chinese Avg. | Avg. |
 | ----------------- | :------------: | :------------: | :------------: | :-------------: | :-------------: | :------------: | :------------: |
 | Jais-30B-v3       | 42.53        | 30.96        | 36.75        | 25.26         | 22.17         | 23.72        |30.23|
-| **AceGPT-v2-8B** | 65.48        | 60.49        | 62.99        | 53.44         | 50.37         | 51.91        |57.45|
+| **MgGPT-8B** | 65.48        | 60.49        | 62.99        | 53.44         | 50.37         | 51.91        |57.45|
 | Llama3-8B         | 66.57        | 65.92        | 66.25        | 50.70         | 49.78         | 50.24        |58.24|
 | ChatGPT 3.5 Turbo | 69.03        | 83.00        | 76.02        | 53.90         | 52.50         | 53.20        |64.60|
 | Qwen1.5-7B        | 62.15        | 82.19        | 72.17        | 71.79         | 73.61         | 72.70        |72.44|
-| **AceGPT-v2-70B** | 76.71        | 80.48        | 78.60        | 68.97         | 66.87         | 67.92        |73.26|
+| **MgGPT-70B** | 76.71        | 80.48        | 78.60        | 68.97         | 66.87         | 67.92        |73.26|
 | GPT-4             | **83.00**    | **91.00**    | **87.00**    | 71.00         | 69.90         | 70.45        |78.73|
 | Llama3-70B        | <u>79.34</u> | 84.76        | <u>82.05</u> | 68.29         | 67.21         | 67.75        |74.90|
 | Qwen1.5-32B       | 75.10        | 83.29        | 79.20        | **83.12**     | <u>82.68</u>  | <u>82.90</u> |81.05|
-| **AceGPT-v2-32B** | 74.52        | <u>88.68</u> | 81.60        | 81.36         | 82.41         | 81.89        |<u>81.74</u>|
+| **MgGPT-32B** | 74.52        | <u>88.68</u> | 81.60        | 81.36         | 82.41         | 81.89        |<u>81.74</u>|
 | Qwen1.5-72B       | 75.78        | 88.23        | 82.01        | <u>83.11</u>  | **83.04**     | **83.08**    |**82.54**|
 
 
@@ -76,7 +76,7 @@ Benchmarks for English and Chinese are conducted using the [OpenCompass](https:/
 " C\n\nسؤال: ما هي الحجج"
 
 
-# Reference
+<!-- # Reference
 ```
 @inproceedings{liang2024alignment,
   title={Alignment at Pre-training! Towards Native Alignment for Arabic {LLM}s},
@@ -93,4 +93,4 @@ Benchmarks for English and Chinese are conducted using the [OpenCompass](https:/
   journal={},
   year={2024}
 }
-```
+``` -->