Improve language tag

README.md

@@ -1,70 +1,82 @@
----
-base_model: Qwen/Qwen2.5-0.5B
-language:
-- en
-library_name: transformers
-license: apache-2.0
-license_link: https://huggingface.co/Qwen/Qwen2.5-0.5B/blob/main/LICENSE
-pipeline_tag: text-generation
-tags:
-- mlc-ai
-- MLC-Weight-Conversion
----
----
-library_name: mlc-llm
-base_model: Qwen/Qwen2.5-0.5B
-tags:
-- mlc-llm
-- web-llm
----
-
-# AMKCode/Qwen2.5-0.5B-q4f16_1-MLC
-
-This is the [Qwen2.5-0.5B](https://huggingface.co/Qwen/Qwen2.5-0.5B) model in MLC format `q4f16_1`.
-The conversion was done using the [MLC-Weight-Conversion](https://huggingface.co/spaces/mlc-ai/MLC-Weight-Conversion) space.
-The model can be used for projects [MLC-LLM](https://github.com/mlc-ai/mlc-llm) and [WebLLM](https://github.com/mlc-ai/web-llm).
-
-## Example Usage
-
-Here are some examples of using this model in MLC LLM.
-Before running the examples, please install MLC LLM by following the [installation documentation](https://llm.mlc.ai/docs/install/mlc_llm.html#install-mlc-packages).
-
-### Chat
-
-In command line, run
-```bash
-mlc_llm chat HF://mlc-ai/AMKCode/Qwen2.5-0.5B-q4f16_1-MLC
-```
-
-### REST Server
-
-In command line, run
-```bash
-mlc_llm serve HF://mlc-ai/AMKCode/Qwen2.5-0.5B-q4f16_1-MLC
-```
-
-### Python API
-
-```python
-from mlc_llm import MLCEngine
-
-# Create engine
-model = "HF://mlc-ai/AMKCode/Qwen2.5-0.5B-q4f16_1-MLC"
-engine = MLCEngine(model)
-
-# Run chat completion in OpenAI API.
-for response in engine.chat.completions.create(
-    messages=[{"role": "user", "content": "What is the meaning of life?"}],
-    model=model,
-    stream=True,
-):
-    for choice in response.choices:
-        print(choice.delta.content, end="", flush=True)
-print("\n")
-
-engine.terminate()
-```
-
-## Documentation
-
+---
+base_model: Qwen/Qwen2.5-0.5B
+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/blob/main/LICENSE
+pipeline_tag: text-generation
+tags:
+- mlc-ai
+- MLC-Weight-Conversion
+---
+---
+library_name: mlc-llm
+base_model: Qwen/Qwen2.5-0.5B
+tags:
+- mlc-llm
+- web-llm
+---
+
+# AMKCode/Qwen2.5-0.5B-q4f16_1-MLC
+
+This is the [Qwen2.5-0.5B](https://huggingface.co/Qwen/Qwen2.5-0.5B) model in MLC format `q4f16_1`.
+The conversion was done using the [MLC-Weight-Conversion](https://huggingface.co/spaces/mlc-ai/MLC-Weight-Conversion) space.
+The model can be used for projects [MLC-LLM](https://github.com/mlc-ai/mlc-llm) and [WebLLM](https://github.com/mlc-ai/web-llm).
+
+## Example Usage
+
+Here are some examples of using this model in MLC LLM.
+Before running the examples, please install MLC LLM by following the [installation documentation](https://llm.mlc.ai/docs/install/mlc_llm.html#install-mlc-packages).
+
+### Chat
+
+In command line, run
+```bash
+mlc_llm chat HF://mlc-ai/AMKCode/Qwen2.5-0.5B-q4f16_1-MLC
+```
+
+### REST Server
+
+In command line, run
+```bash
+mlc_llm serve HF://mlc-ai/AMKCode/Qwen2.5-0.5B-q4f16_1-MLC
+```
+
+### Python API
+
+```python
+from mlc_llm import MLCEngine
+
+# Create engine
+model = "HF://mlc-ai/AMKCode/Qwen2.5-0.5B-q4f16_1-MLC"
+engine = MLCEngine(model)
+
+# Run chat completion in OpenAI API.
+for response in engine.chat.completions.create(
+    messages=[{"role": "user", "content": "What is the meaning of life?"}],
+    model=model,
+    stream=True,
+):
+    for choice in response.choices:
+        print(choice.delta.content, end="", flush=True)
+print("\n")
+
+engine.terminate()
+```
+
+## Documentation
+
 For more information on MLC LLM project, please visit our [documentation](https://llm.mlc.ai/docs/) and [GitHub repo](http://github.com/mlc-ai/mlc-llm).