readme.md fixed, hopefully

README.md

@@ -1,13 +1,14 @@
 ---
-language: gr
-- 
-thumbnail: https://huggingface.co/macedonizer/gr-roberta-base/lets-talk-about-nlp-gr.jpg
+language: 
+- mk
+thumbnail: https://huggingface.co/macedonizer/mk-roberta-base/blaze-koneski.jpg
 license: Apache 2.0
 datasets:
-- wiki-gr
+- wiki-mk
+- time-mk-news-2010-2015
 ---
 
-# gr-gpt2
+# mk-gpt2
 Test the whole generation capabilities here: https://transformer.huggingface.co/doc/gpt2-large
 Pretrained model on English language using a causal language modeling (CLM) objective. It was introduced in
 [this paper](https://d4mucfpksywv.cloudfront.net/better-language-models/language_models_are_unsupervised_multitask_learners.pdf)
@@ -31,10 +32,10 @@ Here is how to use this model to get the features of a given text in PyTorch:
 import random
 from transformers import AutoTokenizer, AutoModelWithLMHead
 
-tokenizer = AutoTokenizer.from_pretrained('macedonizer/gr-gpt2') \
-model = AutoModelWithLMHead.from_pretrained('macedonizer/gr-gpt2')
+tokenizer = AutoTokenizer.from_pretrained('macedonizer/mk-gpt2') \
+model = AutoModelWithLMHead.from_pretrained('macedonizer/mk-gpt2')
 
-input_text = 'Η Αθήνα είναι'
+input_text = 'Скопје е '
 
 if len(input_text) == 0: \
     encoded_input = tokenizer(input_text, return_tensors="pt") \