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README.md

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+# NepaliBERT(Phase 1) 
+NEPALIBERT is a state-of-the-art language model for Nepali based on the BERT model. The model is trained using a masked language modeling (MLM). 
+
+# Loading the model and tokenizer 
+1. clone the model repo 
+```
+git lfs install
+git clone https://huggingface.co/Rajan/NepaliBERT
+```
+2. Loading the Tokenizer 
+```
+from transformers import BertTokenizer
+vocab_file_dir = './NepaliBERT/' 
+tokenizer = BertTokenizer.from_pretrained(vocab_file_dir,
+                                        strip_accents=False,
+                                         clean_text=False )
+```
+3. Loading the model:
+```
+from transformers import BertForMaskedLM
+model = BertForMaskedLM.from_pretrained('./NepaliBERT')
+```
+
+The easiest way to check whether our language model is learning anything interesting is via the ```FillMaskPipeline```.
+
+Pipelines are simple wrappers around tokenizers and models, and the 'fill-mask' one will let you input a sequence containing a masked token (here, [mask]) and return a list of the most probable filled sequences, with their probabilities.
+
+```
+from transformers import pipeline
+
+fill_mask = pipeline(
+    "fill-mask",
+    model=model,
+    tokenizer=tokenizer
+)
+```
+For more info visit the [GITHUB🤗](https://github.com/R4j4n/NepaliBERT)