Initial commit

README.md

@@ -0,0 +1,52 @@
+---
+language: 
+- bn
+licenses:
+- cc-by-nc-sa-4.0
+---
+
+# BanglaBERT
+
+This repository contains the pretrained discriminator checkpoint of the model **BanglaBERT**. This is an [ELECTRA](https://openreview.net/pdf?id=r1xMH1BtvB) discriminator model pretrained with the Replaced Token Detection (RTD) objective. Finetuned models using this checkpoint achieve state-of-the-art results on many of the NLP tasks in bengali. 
+
+For finetuning on different downstream tasks such as `Sentiment classification`, `Named Entity Recognition`, `Natural Language Inference` etc., refer to the scripts in the official [repository](https://https://github.com/csebuetnlp/banglabert).
+
+## Using this model as a discriminator in `transformers` (tested on 4.11.0.dev0)
+
+```python
+from transformers import ElectraForPreTraining, ElectraTokenizerFast
+from normalizer import normalize # pip install git+https://github.com/abhik1505040/normalizer
+import torch
+
+model = ElectraForPreTraining.from_pretrained("banglabert")
+tokenizer = ElectraTokenizerFast.from_pretrained("banglabert")
+
+original_sentence = "আমি কৃতজ্ঞ কারণ আপনি আমার জন্য অনেক কিছু করেছেন।"
+fake_sentence = "আমি হতাশ কারণ আপনি আমার জন্য অনেক কিছু করেছেন।"
+fake_sentence = normalize(fake_sentence) # this normalization step is required before tokenizing the text
+
+fake_tokens = tokenizer.tokenize(fake_sentence)
+fake_inputs = tokenizer.encode(fake_sentence, return_tensors="pt")
+discriminator_outputs = model(fake_inputs).logits
+predictions = torch.round((torch.sign(discriminator_outputs) + 1) / 2)
+
+[print("%7s" % token, end="") for token in fake_tokens]
+print("\n" + "-" * 50)
+[print("%7s" % int(prediction), end="") for prediction in predictions.squeeze().tolist()[1:-1]]
+print("\n" + "-" * 50)
+```
+
+## Citation
+
+If you use this model, please cite the following paper:
+```
+@misc{bhattacharjee2021banglabert,
+      title={BanglaBERT: Combating Embedding Barrier in Multilingual Models for Low-Resource Language Understanding}, 
+      author={Abhik Bhattacharjee and Tahmid Hasan and Kazi Samin and Md Saiful Islam and M. Sohel Rahman and Anindya Iqbal and Rifat Shahriyar},
+      year={2021},
+      eprint={2101.00204},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```
+

config.json

@@ -0,0 +1,25 @@
+{
+  "architectures": [
+    "ElectraForPreTraining"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "embedding_size": 768,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "electra",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "summary_activation": "gelu",
+  "summary_last_dropout": 0.1,
+  "summary_type": "first",
+  "summary_use_proj": true,
+  "type_vocab_size": 2,
+  "vocab_size": 32000
+}
+

pytorch_model.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9d33f519f42705d54e65fc1601644a6f4562c3462f96943b32b4184536130f98
+size 442560329

special_tokens_map.json

@@ -0,0 +1 @@
+{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}

tokenizer_config.json

@@ -0,0 +1 @@
+{"do_lower_case": false, "tokenize_chinese_chars": false, "special_tokens_map_file": null, "full_tokenizer_file": null}