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README.md

@@ -1,3 +1,31 @@
----
-license: cc-by-nc-4.0
----
+---
+language:
+- bn
+tags:
+- bert
+- bangla
+- mlm
+- nsp
+---
+
+# BERT base model for Bangla
+
+Pretrained [BERT](https://arxiv.org/abs/1810.04805) model for Bangla. The model was trained on Masked Language Modeling (MLM) and Next Sentence Prediction (NSP) tasks.
+
+## Model Details
+
+This model is based on the BERT-Base architecture with 12 layers, 768 hidden size, 12 attention heads, and 110 million parameters. The model was trained on a corpus of 39 GB Bangla text data with a vocabulary size of 50k tokens. The model was trained for 1 million steps with a batch size of 440 and a learning rate of 5e-5. The model was trained on two NVIDIA GeForce A40 GPUs.
+
+## How to use
+
+```python
+from transformers import AutoModel, AutoTokenizer
+
+model = AutoModel.from_pretrained("eblict/BERT-Base")
+tokenizer = AutoTokenizer.from_pretrained("eblict/BERT-Base")
+
+text = "আমি বাংলায় পড়ি।"
+
+tokenized_text = tokenizer(text, return_tensors="pt")
+outputs = model(**tokenized_text)
+```