Updating README with 2.0 in name

README.md

@@ -40,8 +40,8 @@ This model currently needs a custom wrapper from `modeling_ltgbert.py`, you shou
 import torch
 from transformers import AutoTokenizer, AutoModelForMaskedLM
 
-tokenizer = AutoTokenizer.from_pretrained("HPLT/hplt_bert_base_spa-Latn")
-model = AutoModelForMaskedLM.from_pretrained("HPLT/hplt_bert_base_spa-Latn", trust_remote_code=True)
+tokenizer = AutoTokenizer.from_pretrained("HPLT/hplt_bert_base_2_0_spa-Latn")
+model = AutoModelForMaskedLM.from_pretrained("HPLT/hplt_bert_base_2_0_spa-Latn", trust_remote_code=True)
 
 mask_id = tokenizer.convert_tokens_to_ids("[MASK]")
 input_text = tokenizer("It's a beautiful[MASK].", return_tensors="pt")
@@ -60,13 +60,13 @@ We are releasing 10 intermediate checkpoints for each model at intervals of ever
 
 You can load a specific model revision with `transformers` using the argument `revision`:
 ```python
-model = AutoModelForMaskedLM.from_pretrained("HPLT/hplt_bert_base_spa-Latn", revision="step21875", trust_remote_code=True)
+model = AutoModelForMaskedLM.from_pretrained("HPLT/hplt_bert_base_2_0_spa-Latn", revision="step21875", trust_remote_code=True)
 ```
 
 You can access all the revisions for the models with the following code:
 ```python
 from huggingface_hub import list_repo_refs
-out = list_repo_refs("HPLT/hplt_bert_base_spa-Latn")
+out = list_repo_refs("HPLT/hplt_bert_base_2_0_spa-Latn")
 print([b.name for b in out.branches])
 ```