readme

README.md

@@ -49,14 +49,14 @@ GLM-4V-9B。**GLM-4V-9B** 具备 1120 * 1120 高分辨率下的中英双语多
 
 在六个多语言数据集上对 GLM-4-9B-Chat 和 Llama-3-8B-Instruct 进行了测试，测试结果及数据集对应选取语言如下表
 
-| Dataset     | Llama-3-8B-Instruct | GLM-4-9B-Chat |                                           Languages                                            
+| Dataset     | Llama-3-8B-Instruct | GLM-4-9B-Chat |                                           Languages                                            |
 |:------------|:-------------------:|:-------------:|:----------------------------------------------------------------------------------------------:|
-| M-MMLU      |        49.6         |     56.6      |                                              all                                               
-| FLORES      |        25.0         |     28.8      | ru, es, de, fr, it, pt, pl, ja, nl, ar, tr, cs, vi, fa, hu, el, ro, sv, uk, fi, ko, da, bg, no 
-| MGSM        |        54.0         |     65.3      |                           zh, en, bn, de, es, fr, ja, ru, sw, te, th                           
-| XWinograd   |        61.7         |     73.1      |                                     zh, en, fr, jp, ru, pt                                     
-| XStoryCloze |        84.7         |     90.7      |                           zh, en, ar, es, eu, hi, id, my, ru, sw, te                           
-| XCOPA       |        73.3         |     80.1      |                           zh, et, ht, id, it, qu, sw, ta, th, tr, vi                           
+| M-MMLU      |        49.6         |     56.6      |                                              all                                               |
+| FLORES      |        25.0         |     28.8      | ru, es, de, fr, it, pt, pl, ja, nl, ar, tr, cs, vi, fa, hu, el, ro, sv, uk, fi, ko, da, bg, no |
+| MGSM        |        54.0         |     65.3      |                           zh, en, bn, de, es, fr, ja, ru, sw, te, th                           |
+| XWinograd   |        61.7         |     73.1      |                                     zh, en, fr, jp, ru, pt                                     |
+| XStoryCloze |        84.7         |     90.7      |                           zh, en, ar, es, eu, hi, id, my, ru, sw, te                           |
+| XCOPA       |        73.3         |     80.1      |                           zh, et, ht, id, it, qu, sw, ta, th, tr, vi                           |
 
 ### 工具调用能力
 

README_en.md

@@ -1,18 +1,3 @@
----
-license: other
-license_name: glm-4
-license_link: https://huggingface.co/THUDM/glm-4-9b-chat/blob/main/LICENSE
-
-language:
-  - zh
-  - en
-tags:
-  - glm
-  - chatglm
-  - thudm
-inference: false
----
-
 # GLM-4-9B-Chat
 
 ## Model Introduction
@@ -132,7 +117,7 @@ from vllm import LLM, SamplingParams
 # If you encounter OOM, it is recommended to reduce max_model_len or increase tp_size
 max_model_len, tp_size = 131072, 1
 model_name = "THUDM/glm-4-9b-chat"
-prompt = [{"role": "user", "content": "你好"}]
+prompt = [{"role": "user", "content": "hello"}]
 
 tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
 llm = LLM(