Upload README.md with huggingface_hub

README.md

@@ -0,0 +1,63 @@
+
+---
+license: apache-2.0
+datasets:
+- allenai/MADLAD-400
+language:
+- bn
+base_model:
+- Qwen/Qwen3-14B-Base
+library_name: transformers
+---
+# Qwen3 14B Base for Bengali: Vocabulary expansion
+
+This model is built on top of Qwen3 14B Base adapted for Bengali using 500M target language tokens sampled from MADLAD-400. It has an additional target vocabulary of 10K.
+
+## Model Details
+
+* **Vocabulary**: This model has an additional target vocabulary of 10K.
+* **Target vocabulary initialization**: The target weights of the embedding and LM head were initialized using mean initialization.
+* **Training**: This model was continually pre-trained on 500M target language tokens sampled from MADLAD-400.
+
+
+## Model Description
+
+- **Language:** Bengali
+- **License:** Apache 2.0
+- **Fine-tuned from model:** Qwen/Qwen3-14B-Base
+
+
+## Model Sources
+
+- **Repository:** https://github.com/gucci-j/chat-cve
+- **Paper:** https://arxiv.org/abs/2412.11704
+
+
+## How to Get Started with the Model
+Use the code below to get started with the model.
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+model = AutoModelForCausalLM.from_pretrained(
+    "atsuki-yamaguchi/Qwen3-14B-Base-bn-madlad-mean-tuned"
+)
+tokenizer = AutoTokenizer.from_pretrained(
+    "atsuki-yamaguchi/Qwen3-14B-Base-bn-madlad-mean-tuned"
+)
+```
+
+
+## Citation
+```
+@article{yamaguchi2025adapting,
+      title={Adapting Chat Language Models Using Only Target Unlabeled Language Data}, 
+      author={Atsuki Yamaguchi and Terufumi Morishita and Aline Villavicencio and Nikolaos Aletras},
+      journal={Transactions on Machine Learning Research},
+      issn={2835-8856},
+      year={2025},
+      url={https://openreview.net/forum?id=6IdoIKowfe},
+      note={}
+}
+```
+
+