Improve language tag (#1)

- Improve language tag (415d10c1bd237c4bd24744c06557743010c16f9c)


Co-authored-by: Loïck BOURDOIS <lbourdois@users.noreply.huggingface.co>

README.md

@@ -1,34 +1,46 @@
----
-license: apache-2.0
-license_link: https://huggingface.co/Qwen/Qwen2.5-3B-Instruct-GGUF/blob/main/LICENSE
-language:
-- en
-base_model:
-- Qwen/Qwen2.5-3B-Instruct
-pipeline_tag: text-generation
-quantized_by: mukel
-tags:
-- chat
-- qwen
----
-
-# GGUF models for qwen2.java 
-Pure .gguf Q4_0 and Q8_0 quantizations of Qwen 2.5 models, ready to consume by `qwen2.java`.
-
-In the wild, Q8_0 quantizations are fine, but Q4_0 quantizations are rarely pure e.g. the token embeddings are quantized with Q6_K, instead of Q4_0.  
-A pure Q4_0 quantization can be generated from a high precision (F32, F16, BFLOAT16) .gguf source with the llama-quantize utility from llama.cpp as follows:
-
-```
-./llama-quantize --pure ./Qwen-2.5-7B-Instruct-BF16.gguf ./Qwen-2.5-7B-Instruct-Q4_0.gguf Q4_0
-```
-
-## Introduction
-
-Qwen2.5 is the latest series of Qwen large language models. For Qwen2.5, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters. Qwen2.5 brings the following improvements upon Qwen2:
-
-- Significantly **more knowledge** and has greatly improved capabilities in **coding** and **mathematics**, thanks to our specialized expert models in these domains.
-- Significant improvements in **instruction following**, **generating long texts** (over 8K tokens), **understanding structured data** (e.g, tables), and **generating structured outputs** especially JSON. **More resilient to the diversity of system prompts**, enhancing role-play implementation and condition-setting for chatbots.
-- **Long-context Support** up to 128K tokens and can generate up to 8K tokens.
-- **Multilingual support** for over 29 languages, including Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, Korean, Vietnamese, Thai, Arabic, and more. 
-
-For more details, please refer to our [blog](https://qwenlm.github.io/blog/qwen2.5/), [GitHub](https://github.com/QwenLM/Qwen2.5), and [Documentation](https://qwen.readthedocs.io/en/latest/).
+---
+license: apache-2.0
+license_link: https://huggingface.co/Qwen/Qwen2.5-3B-Instruct-GGUF/blob/main/LICENSE
+language:
+- zho
+- eng
+- fra
+- spa
+- por
+- deu
+- ita
+- rus
+- jpn
+- kor
+- vie
+- tha
+- ara
+base_model:
+- Qwen/Qwen2.5-3B-Instruct
+pipeline_tag: text-generation
+quantized_by: mukel
+tags:
+- chat
+- qwen
+---
+
+# GGUF models for qwen2.java 
+Pure .gguf Q4_0 and Q8_0 quantizations of Qwen 2.5 models, ready to consume by `qwen2.java`.
+
+In the wild, Q8_0 quantizations are fine, but Q4_0 quantizations are rarely pure e.g. the token embeddings are quantized with Q6_K, instead of Q4_0.  
+A pure Q4_0 quantization can be generated from a high precision (F32, F16, BFLOAT16) .gguf source with the llama-quantize utility from llama.cpp as follows:
+
+```
+./llama-quantize --pure ./Qwen-2.5-7B-Instruct-BF16.gguf ./Qwen-2.5-7B-Instruct-Q4_0.gguf Q4_0
+```
+
+## Introduction
+
+Qwen2.5 is the latest series of Qwen large language models. For Qwen2.5, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters. Qwen2.5 brings the following improvements upon Qwen2:
+
+- Significantly **more knowledge** and has greatly improved capabilities in **coding** and **mathematics**, thanks to our specialized expert models in these domains.
+- Significant improvements in **instruction following**, **generating long texts** (over 8K tokens), **understanding structured data** (e.g, tables), and **generating structured outputs** especially JSON. **More resilient to the diversity of system prompts**, enhancing role-play implementation and condition-setting for chatbots.
+- **Long-context Support** up to 128K tokens and can generate up to 8K tokens.
+- **Multilingual support** for over 29 languages, including Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, Korean, Vietnamese, Thai, Arabic, and more. 
+
+For more details, please refer to our [blog](https://qwenlm.github.io/blog/qwen2.5/), [GitHub](https://github.com/QwenLM/Qwen2.5), and [Documentation](https://qwen.readthedocs.io/en/latest/).