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

@@ -1,35 +1,47 @@
----
-base_model:
-- Qwen/Qwen2.5-1.5B-Instruct
-- google/siglip-so400m-patch14-384
-datasets:
-- weizhiwang/Open-Qwen2VL-Data
-- MAmmoTH-VL/MAmmoTH-VL-Instruct-12M
-language:
-- en
-license: cc
-pipeline_tag: image-text-to-text
----
-
-# Model Card for Open-Qwen2VL-base
-
-Open-Qwen2VL-base is a pre-trained base multimodal model that takes images and text as input and produces text as output. This model is described in the paper [Open-Qwen2VL: Compute-Efficient Pre-Training of Fully-Open Multimodal LLMs on Academic Resources](https://huggingface.co/papers/2504.00595).  The code is available at [https://github.com/Victorwz/Open-Qwen2VL](https://github.com/Victorwz/Open-Qwen2VL).
-
-## Updates 
-- [4/1/2025] The codebase, model, data, and paper are released.
-
-<!-- ## Model Details -->
-
-## How to Use
-
-The base model is released for further fine-tuning on public SFT data or customized SFT data. It is not appropriate for normal task completions.
-
-## Citation
-```bibtex
-@article{Open-Qwen2VL,
-    title={Open-Qwen2VL: Compute-Efficient Pre-Training of Fully-Open Multimodal LLMs on Academic Resources},
-    author={Wang, Weizhi and Tian, Yu and Yang, Linjie and Wang, Heng and Yan, Xifeng},
-    journal={arXiv preprint arXiv:2504.00595},
-    year={2025}
-  }
+---
+base_model:
+- Qwen/Qwen2.5-1.5B-Instruct
+- google/siglip-so400m-patch14-384
+datasets:
+- weizhiwang/Open-Qwen2VL-Data
+- MAmmoTH-VL/MAmmoTH-VL-Instruct-12M
+language:
+- zho
+- eng
+- fra
+- spa
+- por
+- deu
+- ita
+- rus
+- jpn
+- kor
+- vie
+- tha
+- ara
+license: cc
+pipeline_tag: image-text-to-text
+---
+
+# Model Card for Open-Qwen2VL-base
+
+Open-Qwen2VL-base is a pre-trained base multimodal model that takes images and text as input and produces text as output. This model is described in the paper [Open-Qwen2VL: Compute-Efficient Pre-Training of Fully-Open Multimodal LLMs on Academic Resources](https://huggingface.co/papers/2504.00595).  The code is available at [https://github.com/Victorwz/Open-Qwen2VL](https://github.com/Victorwz/Open-Qwen2VL).
+
+## Updates 
+- [4/1/2025] The codebase, model, data, and paper are released.
+
+<!-- ## Model Details -->
+
+## How to Use
+
+The base model is released for further fine-tuning on public SFT data or customized SFT data. It is not appropriate for normal task completions.
+
+## Citation
+```bibtex
+@article{Open-Qwen2VL,
+    title={Open-Qwen2VL: Compute-Efficient Pre-Training of Fully-Open Multimodal LLMs on Academic Resources},
+    author={Wang, Weizhi and Tian, Yu and Yang, Linjie and Wang, Heng and Yan, Xifeng},
+    journal={arXiv preprint arXiv:2504.00595},
+    year={2025}
+  }
 ...