Add README.md

README.md

@@ -8,8 +8,8 @@ datasets:
 - bookcorpus
 - wikipedia
 ---
-# MultiBERTs Seed ${ckpt} (uncased)
-Seed ${ckpt} pretrained BERT model on English language using a masked language modeling (MLM) objective. It was introduced in
+# MultiBERTs Seed 0 (uncased)
+Seed 0 pretrained BERT model on English language using a masked language modeling (MLM) objective. It was introduced in
 [this paper](https://arxiv.org/pdf/2106.16163.pdf) and first released in
 [this repository](https://github.com/google-research/language/tree/master/language/multiberts). This model is uncased: it does not make a difference
 between english and English.
@@ -42,7 +42,7 @@ generation you should look at model like GPT2.
 Here is how to use this model to get the features of a given text in PyTorch:
 ```python
 from transformers import BertTokenizer, BertModel
-tokenizer = BertTokenizer.from_pretrained('multiberts-seed-${ckpt}')
+tokenizer = BertTokenizer.from_pretrained('multiberts-seed-'0'')
 model = BertModel.from_pretrained("bert-base-uncased")
 text = "Replace me by any text you'd like."
 encoded_input = tokenizer(text, return_tensors='pt')