diff --git a/python-lib/macro/model_configurations.py b/python-lib/macro/model_configurations.py
index 4e47f2d..fa02acb 100644
--- a/python-lib/macro/model_configurations.py
+++ b/python-lib/macro/model_configurations.py
@@ -1,3 +1,15 @@
+from transformers import (tokenization_bert,
+                          tokenization_gpt2,
+                          tokenization_transfo_xl,
+                          tokenization_xlnet,
+                          tokenization_roberta,
+                          tokenization_distilbert,
+                          tokenization_ctrl,
+                          tokenization_camembert,
+                          tokenization_albert,
+                          tokenization_t5,
+                          tokenization_bart)
+
 NON_TRANSFORMER_MODELS = ["word2vec","fasttext","glove","elmo","use"]
 TRANSFORMERS_MODELS = ['bert-base-uncased', 'bert-large-uncased', 'bert-base-cased', 'bert-large-cased', 'bert-base-multilingual-uncased', 'bert-base-multilingual-cased', 'bert-base-chinese', 'bert-base-german-cased', 'bert-large-uncased-whole-word-masking', 'bert-large-cased-whole-word-masking', 'bert-large-uncased-whole-word-masking-finetuned-squad', 'bert-large-cased-whole-word-masking-finetuned-squad', 'bert-base-cased-finetuned-mrpc', 'bert-base-german-dbmdz-cased', 'bert-base-german-dbmdz-uncased', 'cl-tohoku/bert-base-japanese', 'cl-tohoku/bert-base-japanese-whole-word-masking', 'cl-tohoku/bert-base-japanese-char', 'cl-tohoku/bert-base-japanese-char-whole-word-masking', 'TurkuNLP/bert-base-finnish-cased-v1', 'TurkuNLP/bert-base-finnish-uncased-v1', 'wietsedv/bert-base-dutch-cased', 'facebook/bart-large', 'facebook/bart-large-mnli', 'facebook/bart-large-cnn', 'facebook/mbart-large-en-ro', 'openai-gpt', 'transfo-xl-wt103', 'gpt2', 'gpt2-medium', 'gpt2-large', 'gpt2-xl', 'distilgpt2', 'ctrl', 'xlnet-base-cased', 'xlnet-large-cased', 'xlm-mlm-en-2048', 'xlm-mlm-ende-1024', 'xlm-mlm-enfr-1024', 'xlm-mlm-enro-1024', 'xlm-mlm-tlm-xnli15-1024', 'xlm-mlm-xnli15-1024', 'xlm-clm-enfr-1024', 'xlm-clm-ende-1024', 'xlm-mlm-17-1280', 'xlm-mlm-100-1280', 'roberta-base', 'roberta-large', 'roberta-large-mnli', 'distilroberta-base', 'roberta-base-openai-detector', 'roberta-large-openai-detector', 'distilbert-base-uncased', 'distilbert-base-uncased-distilled-squad', 'distilbert-base-cased', 'distilbert-base-cased-distilled-squad', 'distilbert-base-german-cased', 'distilbert-base-multilingual-cased', 'albert-base-v1', 'albert-large-v1', 'albert-xlarge-v1', 'albert-xxlarge-v1', 'albert-base-v2', 'albert-large-v2', 'albert-xlarge-v2', 'albert-xxlarge-v2', 'camembert-base', 't5-small', 't5-base', 't5-large', 'xlm-roberta-base', 'xlm-roberta-large', 'flaubert/flaubert_small_cased', 'flaubert/flaubert_base_uncased', 'flaubert/flaubert_base_cased', 'flaubert/flaubert_large_cased', 'allenai/longformer-base-4096', 'allenai/longformer-large-4096']
 MODEL_CONFIFURATIONS = {
@@ -1077,4 +1089,58 @@
 
     }
 
+BART_URL_MAP = {
+    'vocab_file': {model: tokenization_bart.vocab_url for model in tokenization_bart._all_bart_models},
+    'merges_file': {model: tokenization_bart.merges_url for model in tokenization_bart._all_bart_models}
+}
+BART_FILE_NAMES = tokenization_roberta.VOCAB_FILES_NAMES
+
+
+TOKENIZER_CONFIGURATIONS = {
+    'BERT': {
+        'url_map': tokenization_bert.PRETRAINED_VOCAB_FILES_MAP,
+        'file_names': tokenization_bert.VOCAB_FILES_NAMES
+    },
+    'GPT-2': {
+        'url_map': tokenization_gpt2.PRETRAINED_VOCAB_FILES_MAP,
+        'file_names': tokenization_gpt2.VOCAB_FILES_NAMES
+    },
+    'CamemBERT': {
+        'url_map': tokenization_camembert.PRETRAINED_VOCAB_FILES_MAP,
+        'file_names': tokenization_camembert.VOCAB_FILES_NAMES
+    },
+    'ALBERT': {
+        'url_map': tokenization_albert.PRETRAINED_VOCAB_FILES_MAP,
+        'file_names': tokenization_albert.VOCAB_FILES_NAMES
+    },
+    'CTRL': {
+        'url_map': tokenization_ctrl.PRETRAINED_VOCAB_FILES_MAP,
+        'file_names': tokenization_ctrl.VOCAB_FILES_NAMES
+    },
+    'DistilBERT': {
+        'url_map': tokenization_distilbert.PRETRAINED_VOCAB_FILES_MAP,
+        'file_names': tokenization_distilbert.VOCAB_FILES_NAMES
+    },
+    'RoBERTa': {
+        'url_map': tokenization_roberta.PRETRAINED_VOCAB_FILES_MAP,
+        'file_names': tokenization_roberta.VOCAB_FILES_NAMES
+    },
+    'Bart': {
+        'url_map': BART_URL_MAP,
+        'file_names': BART_FILE_NAMES
+    },
+    'T5': {
+        'url_map': tokenization_t5.PRETRAINED_VOCAB_FILES_MAP,
+        'file_names': tokenization_t5.VOCAB_FILES_NAMES
+    },
+    'Transformer-XL': {
+        'url_map': tokenization_transfo_xl.PRETRAINED_VOCAB_FILES_MAP,
+        'file_names': tokenization_transfo_xl.VOCAB_FILES_NAMES
+    },
+    'XLNet': {
+        'url_map': tokenization_xlnet.PRETRAINED_VOCAB_FILES_MAP,
+        'file_names': tokenization_xlnet.VOCAB_FILES_NAMES
+    },
+}
+
 
diff --git a/python-lib/macro/model_downloaders.py b/python-lib/macro/model_downloaders.py
index 927f359..f4ec298 100644
--- a/python-lib/macro/model_downloaders.py
+++ b/python-lib/macro/model_downloaders.py
@@ -8,7 +8,7 @@
 import io
 import zipfile
 import logging
-from macro.model_configurations import MODEL_CONFIFURATIONS
+from macro.model_configurations import MODEL_CONFIFURATIONS, TOKENIZER_CONFIGURATIONS
 import time
 from transformers.file_utils import (S3_BUCKET_PREFIX,
                                     CLOUDFRONT_DISTRIB_PREFIX,
@@ -21,7 +21,7 @@
 
 WORD2VEC_BASE_URL = "http://vectors.nlpl.eu/repository/20/{}.zip"
 FASTTEXT_BASE_URL = "https://dl.fbaipublicfiles.com/fasttext/vectors-crawl/cc.{}.300.vec.gz"
-HG_FILENAMES = ["pytorch_model.bin","config.json","vocab.txt"]
+HG_FILENAMES = ["pytorch_model.bin", "config.json"]
 
 class BaseDownloader(object):
     def __init__(self,folder,macro_inputs,proxy,progress_callback):
@@ -293,6 +293,16 @@ def run(self):
                 bytes_so_far = self.download_plain(response, bytes_so_far)
             elif response.status_code == 404:
                 pass
+        tokenizer_dict = TOKENIZER_CONFIGURATIONS[self.embedding_family]
+        for file_type in tokenizer_dict['url_map'].keys():
+            self.archive_name = self.language + '/' + self.embedding_family + '/' + self.model_shortcut_name.replace("/","_") + '/' + tokenizer_dict['file_names'][file_type]
+            download_link = tokenizer_dict['url_map'][file_type][self.model_shortcut_name]
+            response = self.get_stream(download_link)
+            if response.status_code == 200:
+                bytes_so_far = self.download_plain(response, bytes_so_far)
+            elif response.status_code == 404:
+                pass
+
 
     def get_file_size(self, response=None):
         total_size = 0
@@ -303,6 +313,14 @@ def get_file_size(self, response=None):
                 total_size += int(response.headers.get('content-length'))
             elif response.status_code == 404:
                 total_size += 0
+        tokenizer_dict = TOKENIZER_CONFIGURATIONS[self.embedding_family]
+        for file_type in tokenizer_dict['url_map'].keys():
+            download_link = tokenizer_dict['url_map'][file_type][self.model_shortcut_name]
+            response = self.get_stream(download_link)
+            if response.status_code == 200:
+                total_size += int(response.headers.get('content-length'))
+            elif response.status_code == 404:
+                total_size += 0
         return total_size