Improve language tag

Hi! As the model is multilingual, this is a PR to add other languages than English to the language tag to improve the referencing. Note that 29 languages are announced in the README, but only 13 are explicitly listed. I was therefore only able to add these 13 languages.

README.md

@@ -1,67 +1,79 @@
----
-base_model: Qwen/Qwen2.5-0.5B-Instruct
-language:
-- en
-library_name: transformers
-license: apache-2.0
-license_link: https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct/blob/main/LICENSE
-pipeline_tag: text-generation
-tags:
-- chat
-- openvino
-- openvino-export
----
-
-This model was converted to OpenVINO from [`Qwen/Qwen2.5-0.5B-Instruct`](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct) using [optimum-intel](https://github.com/huggingface/optimum-intel)
-via the [export](https://huggingface.co/spaces/echarlaix/openvino-export) space.
-
-First make sure you have optimum-intel installed:
-
-```bash
-pip install optimum[openvino]
-```
-
-To load your model you can do as follows:
-In huggingface space
-app.py
-```python
-import gradio as gr
-from huggingface_hub import InferenceClient
-from optimum.intel import OVModelForCausalLM
-from transformers import AutoTokenizer, pipeline
-
-# 載入模型和標記器
-model_id = "HelloSun/Qwen2.5-0.5B-Instruct-openvino"
-model = OVModelForCausalLM.from_pretrained(model_id)
-tokenizer = AutoTokenizer.from_pretrained(model_id)
-
-# 建立生成管道
-pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
-
-def respond(message, history):
-    # 將當前訊息與歷史訊息合併
-    #input_text = message if not history else history[-1]["content"] + " " + message
-    input_text = message
-    # 獲取模型的回應
-    response = pipe(input_text, max_length=500, truncation=True, num_return_sequences=1)
-    reply = response[0]['generated_text']
-    
-    # 返回新的消息格式
-    print(f"Message: {message}")
-    print(f"Reply: {reply}")
-    return reply
-    
-# 設定 Gradio 的聊天界面
-demo = gr.ChatInterface(fn=respond, title="Chat with Qwen(通義千問) 2.5-0.5B", description="與 HelloSun/Qwen2.5-0.5B-Instruct-openvino 聊天！", type='messages')
-
-if __name__ == "__main__":
-    demo.launch()
-```
-requirements.txt
-```requirements.txt
-huggingface_hub==0.25.2
-optimum[openvino]
-```
-
-
-
+---
+base_model: Qwen/Qwen2.5-0.5B-Instruct
+language:
+- zho
+- eng
+- fra
+- spa
+- por
+- deu
+- ita
+- rus
+- jpn
+- kor
+- vie
+- tha
+- ara
+library_name: transformers
+license: apache-2.0
+license_link: https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct/blob/main/LICENSE
+pipeline_tag: text-generation
+tags:
+- chat
+- openvino
+- openvino-export
+---
+
+This model was converted to OpenVINO from [`Qwen/Qwen2.5-0.5B-Instruct`](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct) using [optimum-intel](https://github.com/huggingface/optimum-intel)
+via the [export](https://huggingface.co/spaces/echarlaix/openvino-export) space.
+
+First make sure you have optimum-intel installed:
+
+```bash
+pip install optimum[openvino]
+```
+
+To load your model you can do as follows:
+In huggingface space
+app.py
+```python
+import gradio as gr
+from huggingface_hub import InferenceClient
+from optimum.intel import OVModelForCausalLM
+from transformers import AutoTokenizer, pipeline
+
+# 載入模型和標記器
+model_id = "HelloSun/Qwen2.5-0.5B-Instruct-openvino"
+model = OVModelForCausalLM.from_pretrained(model_id)
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+
+# 建立生成管道
+pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+def respond(message, history):
+    # 將當前訊息與歷史訊息合併
+    #input_text = message if not history else history[-1]["content"] + " " + message
+    input_text = message
+    # 獲取模型的回應
+    response = pipe(input_text, max_length=500, truncation=True, num_return_sequences=1)
+    reply = response[0]['generated_text']
+    
+    # 返回新的消息格式
+    print(f"Message: {message}")
+    print(f"Reply: {reply}")
+    return reply
+    
+# 設定 Gradio 的聊天界面
+demo = gr.ChatInterface(fn=respond, title="Chat with Qwen(通義千問) 2.5-0.5B", description="與 HelloSun/Qwen2.5-0.5B-Instruct-openvino 聊天！", type='messages')
+
+if __name__ == "__main__":
+    demo.launch()
+```
+requirements.txt
+```requirements.txt
+huggingface_hub==0.25.2
+optimum[openvino]
+```
+
+
+